mirror of
https://github.com/opencv/opencv.git
synced 2024-12-02 07:39:57 +08:00
1473 lines
87 KiB
Python
1473 lines
87 KiB
Python
# This file was automatically generated by SWIG (http://www.swig.org).
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# Version 1.3.40
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#
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# Do not make changes to this file unless you know what you are doing--modify
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# the SWIG interface file instead.
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# This file is compatible with both classic and new-style classes.
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from sys import version_info
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if version_info >= (2,6,0):
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def swig_import_helper():
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from os.path import dirname
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import imp
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fp = None
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try:
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fp, pathname, description = imp.find_module('_ml', [dirname(__file__)])
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except ImportError:
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import _ml
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return _ml
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if fp is not None:
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try:
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_mod = imp.load_module('_ml', fp, pathname, description)
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finally:
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fp.close()
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return _mod
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_ml = swig_import_helper()
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del swig_import_helper
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else:
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import _ml
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del version_info
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try:
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_swig_property = property
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except NameError:
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pass # Python < 2.2 doesn't have 'property'.
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def _swig_setattr_nondynamic(self,class_type,name,value,static=1):
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if (name == "thisown"): return self.this.own(value)
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if (name == "this"):
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if type(value).__name__ == 'SwigPyObject':
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self.__dict__[name] = value
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return
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method = class_type.__swig_setmethods__.get(name,None)
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if method: return method(self,value)
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if (not static) or hasattr(self,name):
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self.__dict__[name] = value
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else:
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raise AttributeError("You cannot add attributes to %s" % self)
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def _swig_setattr(self,class_type,name,value):
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return _swig_setattr_nondynamic(self,class_type,name,value,0)
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def _swig_getattr(self,class_type,name):
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if (name == "thisown"): return self.this.own()
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method = class_type.__swig_getmethods__.get(name,None)
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if method: return method(self)
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raise AttributeError(name)
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def _swig_repr(self):
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try: strthis = "proxy of " + self.this.__repr__()
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except: strthis = ""
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return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)
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try:
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_object = object
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_newclass = 1
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except AttributeError:
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class _object : pass
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_newclass = 0
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class CvRNG_Wrapper(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvRNG_Wrapper, name, value)
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__swig_getmethods__ = {}
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__getattr__ = lambda self, name: _swig_getattr(self, CvRNG_Wrapper, name)
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__repr__ = _swig_repr
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def __init__(self, *args):
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this = _ml.new_CvRNG_Wrapper(*args)
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try: self.this.append(this)
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except: self.this = this
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def ptr(self): return _ml.CvRNG_Wrapper_ptr(self)
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def ref(self): return _ml.CvRNG_Wrapper_ref(self)
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def __eq__(self, *args): return _ml.CvRNG_Wrapper___eq__(self, *args)
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def __ne__(self, *args): return _ml.CvRNG_Wrapper___ne__(self, *args)
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__swig_destroy__ = _ml.delete_CvRNG_Wrapper
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__del__ = lambda self : None;
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CvRNG_Wrapper_swigregister = _ml.CvRNG_Wrapper_swigregister
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CvRNG_Wrapper_swigregister(CvRNG_Wrapper)
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class CvSubdiv2DEdge_Wrapper(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvSubdiv2DEdge_Wrapper, name, value)
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__swig_getmethods__ = {}
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__getattr__ = lambda self, name: _swig_getattr(self, CvSubdiv2DEdge_Wrapper, name)
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__repr__ = _swig_repr
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def __init__(self, *args):
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this = _ml.new_CvSubdiv2DEdge_Wrapper(*args)
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try: self.this.append(this)
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except: self.this = this
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def ptr(self): return _ml.CvSubdiv2DEdge_Wrapper_ptr(self)
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def ref(self): return _ml.CvSubdiv2DEdge_Wrapper_ref(self)
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def __eq__(self, *args): return _ml.CvSubdiv2DEdge_Wrapper___eq__(self, *args)
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def __ne__(self, *args): return _ml.CvSubdiv2DEdge_Wrapper___ne__(self, *args)
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__swig_destroy__ = _ml.delete_CvSubdiv2DEdge_Wrapper
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__del__ = lambda self : None;
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CvSubdiv2DEdge_Wrapper_swigregister = _ml.CvSubdiv2DEdge_Wrapper_swigregister
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CvSubdiv2DEdge_Wrapper_swigregister(CvSubdiv2DEdge_Wrapper)
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import cv
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__doc__ = """Machine Learning
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The Machine Learning library (ML) is a set of classes and functions for
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statistical classification, regression and clustering of data.
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Most of the classification and regression algorithms are implemented as classes.
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As the algorithms have different sets of features (like ability to handle missing
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measurements, or categorical input variables etc.), there is only little common
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ground between the classes. This common ground is defined by the class CvStatModel
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that all the other ML classes are derived from.
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This wrapper was semi-automatically created from the C/C++ headers and therefore
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contains no Python documentation. Because all identifiers are identical to their
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C/C++ counterparts, you can consult the standard manuals that come with OpenCV.
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"""
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CV_LOG2PI = _ml.CV_LOG2PI
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CV_COL_SAMPLE = _ml.CV_COL_SAMPLE
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CV_ROW_SAMPLE = _ml.CV_ROW_SAMPLE
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class CvVectors(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvVectors, name, value)
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__swig_getmethods__ = {}
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__getattr__ = lambda self, name: _swig_getattr(self, CvVectors, name)
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__repr__ = _swig_repr
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__swig_setmethods__["type"] = _ml.CvVectors_type_set
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__swig_getmethods__["type"] = _ml.CvVectors_type_get
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if _newclass:type = _swig_property(_ml.CvVectors_type_get, _ml.CvVectors_type_set)
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__swig_setmethods__["dims"] = _ml.CvVectors_dims_set
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__swig_getmethods__["dims"] = _ml.CvVectors_dims_get
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if _newclass:dims = _swig_property(_ml.CvVectors_dims_get, _ml.CvVectors_dims_set)
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__swig_setmethods__["count"] = _ml.CvVectors_count_set
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__swig_getmethods__["count"] = _ml.CvVectors_count_get
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if _newclass:count = _swig_property(_ml.CvVectors_count_get, _ml.CvVectors_count_set)
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__swig_setmethods__["next"] = _ml.CvVectors_next_set
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__swig_getmethods__["next"] = _ml.CvVectors_next_get
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if _newclass:next = _swig_property(_ml.CvVectors_next_get, _ml.CvVectors_next_set)
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__swig_getmethods__["data"] = _ml.CvVectors_data_get
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if _newclass:data = _swig_property(_ml.CvVectors_data_get)
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def __init__(self):
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this = _ml.new_CvVectors()
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try: self.this.append(this)
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except: self.this = this
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__swig_destroy__ = _ml.delete_CvVectors
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__del__ = lambda self : None;
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CvVectors_swigregister = _ml.CvVectors_swigregister
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CvVectors_swigregister(CvVectors)
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class CvVectors_data(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvVectors_data, name, value)
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__swig_getmethods__ = {}
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__getattr__ = lambda self, name: _swig_getattr(self, CvVectors_data, name)
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__repr__ = _swig_repr
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__swig_setmethods__["ptr"] = _ml.CvVectors_data_ptr_set
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__swig_getmethods__["ptr"] = _ml.CvVectors_data_ptr_get
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if _newclass:ptr = _swig_property(_ml.CvVectors_data_ptr_get, _ml.CvVectors_data_ptr_set)
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__swig_setmethods__["fl"] = _ml.CvVectors_data_fl_set
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__swig_getmethods__["fl"] = _ml.CvVectors_data_fl_get
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if _newclass:fl = _swig_property(_ml.CvVectors_data_fl_get, _ml.CvVectors_data_fl_set)
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__swig_setmethods__["db"] = _ml.CvVectors_data_db_set
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__swig_getmethods__["db"] = _ml.CvVectors_data_db_get
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if _newclass:db = _swig_property(_ml.CvVectors_data_db_get, _ml.CvVectors_data_db_set)
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def __init__(self):
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this = _ml.new_CvVectors_data()
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try: self.this.append(this)
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except: self.this = this
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__swig_destroy__ = _ml.delete_CvVectors_data
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__del__ = lambda self : None;
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CvVectors_data_swigregister = _ml.CvVectors_data_swigregister
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CvVectors_data_swigregister(CvVectors_data)
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CV_VAR_NUMERICAL = _ml.CV_VAR_NUMERICAL
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CV_VAR_ORDERED = _ml.CV_VAR_ORDERED
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CV_VAR_CATEGORICAL = _ml.CV_VAR_CATEGORICAL
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CV_TYPE_NAME_ML_SVM = _ml.CV_TYPE_NAME_ML_SVM
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CV_TYPE_NAME_ML_KNN = _ml.CV_TYPE_NAME_ML_KNN
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CV_TYPE_NAME_ML_NBAYES = _ml.CV_TYPE_NAME_ML_NBAYES
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CV_TYPE_NAME_ML_EM = _ml.CV_TYPE_NAME_ML_EM
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CV_TYPE_NAME_ML_BOOSTING = _ml.CV_TYPE_NAME_ML_BOOSTING
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CV_TYPE_NAME_ML_TREE = _ml.CV_TYPE_NAME_ML_TREE
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CV_TYPE_NAME_ML_ANN_MLP = _ml.CV_TYPE_NAME_ML_ANN_MLP
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CV_TYPE_NAME_ML_CNN = _ml.CV_TYPE_NAME_ML_CNN
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CV_TYPE_NAME_ML_RTREES = _ml.CV_TYPE_NAME_ML_RTREES
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CV_TRAIN_ERROR = _ml.CV_TRAIN_ERROR
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CV_TEST_ERROR = _ml.CV_TEST_ERROR
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class CvStatModel(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvStatModel, name, value)
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__swig_getmethods__ = {}
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__getattr__ = lambda self, name: _swig_getattr(self, CvStatModel, name)
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__repr__ = _swig_repr
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def __init__(self):
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this = _ml.new_CvStatModel()
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try: self.this.append(this)
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except: self.this = this
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__swig_destroy__ = _ml.delete_CvStatModel
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__del__ = lambda self : None;
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def clear(self): return _ml.CvStatModel_clear(self)
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def save(self, *args): return _ml.CvStatModel_save(self, *args)
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def load(self, *args): return _ml.CvStatModel_load(self, *args)
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def write(self, *args): return _ml.CvStatModel_write(self, *args)
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def read(self, *args): return _ml.CvStatModel_read(self, *args)
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CvStatModel_swigregister = _ml.CvStatModel_swigregister
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CvStatModel_swigregister(CvStatModel)
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class CvParamGrid(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvParamGrid, name, value)
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__swig_getmethods__ = {}
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__getattr__ = lambda self, name: _swig_getattr(self, CvParamGrid, name)
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__repr__ = _swig_repr
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SVM_C = _ml.CvParamGrid_SVM_C
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SVM_GAMMA = _ml.CvParamGrid_SVM_GAMMA
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SVM_P = _ml.CvParamGrid_SVM_P
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SVM_NU = _ml.CvParamGrid_SVM_NU
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SVM_COEF = _ml.CvParamGrid_SVM_COEF
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SVM_DEGREE = _ml.CvParamGrid_SVM_DEGREE
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def __init__(self, *args):
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this = _ml.new_CvParamGrid(*args)
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try: self.this.append(this)
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except: self.this = this
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def check(self): return _ml.CvParamGrid_check(self)
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__swig_setmethods__["min_val"] = _ml.CvParamGrid_min_val_set
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__swig_getmethods__["min_val"] = _ml.CvParamGrid_min_val_get
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if _newclass:min_val = _swig_property(_ml.CvParamGrid_min_val_get, _ml.CvParamGrid_min_val_set)
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__swig_setmethods__["max_val"] = _ml.CvParamGrid_max_val_set
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__swig_getmethods__["max_val"] = _ml.CvParamGrid_max_val_get
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if _newclass:max_val = _swig_property(_ml.CvParamGrid_max_val_get, _ml.CvParamGrid_max_val_set)
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__swig_setmethods__["step"] = _ml.CvParamGrid_step_set
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__swig_getmethods__["step"] = _ml.CvParamGrid_step_get
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if _newclass:step = _swig_property(_ml.CvParamGrid_step_get, _ml.CvParamGrid_step_set)
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__swig_destroy__ = _ml.delete_CvParamGrid
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__del__ = lambda self : None;
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CvParamGrid_swigregister = _ml.CvParamGrid_swigregister
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CvParamGrid_swigregister(CvParamGrid)
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class CvNormalBayesClassifier(CvStatModel):
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__swig_setmethods__ = {}
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for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvNormalBayesClassifier, name, value)
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__swig_getmethods__ = {}
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for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
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__getattr__ = lambda self, name: _swig_getattr(self, CvNormalBayesClassifier, name)
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__repr__ = _swig_repr
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__swig_destroy__ = _ml.delete_CvNormalBayesClassifier
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__del__ = lambda self : None;
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def __init__(self, *args):
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this = _ml.new_CvNormalBayesClassifier(*args)
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try: self.this.append(this)
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except: self.this = this
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def train(self, *args): return _ml.CvNormalBayesClassifier_train(self, *args)
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def predict(self, *args): return _ml.CvNormalBayesClassifier_predict(self, *args)
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def clear(self): return _ml.CvNormalBayesClassifier_clear(self)
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def write(self, *args): return _ml.CvNormalBayesClassifier_write(self, *args)
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def read(self, *args): return _ml.CvNormalBayesClassifier_read(self, *args)
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CvNormalBayesClassifier_swigregister = _ml.CvNormalBayesClassifier_swigregister
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CvNormalBayesClassifier_swigregister(CvNormalBayesClassifier)
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class CvKNearest(CvStatModel):
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__swig_setmethods__ = {}
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for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvKNearest, name, value)
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__swig_getmethods__ = {}
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for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
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__getattr__ = lambda self, name: _swig_getattr(self, CvKNearest, name)
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__repr__ = _swig_repr
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__swig_destroy__ = _ml.delete_CvKNearest
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__del__ = lambda self : None;
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def __init__(self, *args):
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this = _ml.new_CvKNearest(*args)
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try: self.this.append(this)
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except: self.this = this
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def train(self, *args): return _ml.CvKNearest_train(self, *args)
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def find_nearest(self, *args): return _ml.CvKNearest_find_nearest(self, *args)
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def clear(self): return _ml.CvKNearest_clear(self)
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def get_max_k(self): return _ml.CvKNearest_get_max_k(self)
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def get_var_count(self): return _ml.CvKNearest_get_var_count(self)
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def get_sample_count(self): return _ml.CvKNearest_get_sample_count(self)
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def is_regression(self): return _ml.CvKNearest_is_regression(self)
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CvKNearest_swigregister = _ml.CvKNearest_swigregister
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CvKNearest_swigregister(CvKNearest)
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class CvSVMParams(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvSVMParams, name, value)
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|
__swig_getmethods__ = {}
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|
__getattr__ = lambda self, name: _swig_getattr(self, CvSVMParams, name)
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__repr__ = _swig_repr
|
|
def __init__(self, *args):
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this = _ml.new_CvSVMParams(*args)
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try: self.this.append(this)
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except: self.this = this
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__swig_setmethods__["svm_type"] = _ml.CvSVMParams_svm_type_set
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|
__swig_getmethods__["svm_type"] = _ml.CvSVMParams_svm_type_get
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|
if _newclass:svm_type = _swig_property(_ml.CvSVMParams_svm_type_get, _ml.CvSVMParams_svm_type_set)
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__swig_setmethods__["kernel_type"] = _ml.CvSVMParams_kernel_type_set
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|
__swig_getmethods__["kernel_type"] = _ml.CvSVMParams_kernel_type_get
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if _newclass:kernel_type = _swig_property(_ml.CvSVMParams_kernel_type_get, _ml.CvSVMParams_kernel_type_set)
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|
__swig_setmethods__["degree"] = _ml.CvSVMParams_degree_set
|
|
__swig_getmethods__["degree"] = _ml.CvSVMParams_degree_get
|
|
if _newclass:degree = _swig_property(_ml.CvSVMParams_degree_get, _ml.CvSVMParams_degree_set)
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|
__swig_setmethods__["gamma"] = _ml.CvSVMParams_gamma_set
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|
__swig_getmethods__["gamma"] = _ml.CvSVMParams_gamma_get
|
|
if _newclass:gamma = _swig_property(_ml.CvSVMParams_gamma_get, _ml.CvSVMParams_gamma_set)
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__swig_setmethods__["coef0"] = _ml.CvSVMParams_coef0_set
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|
__swig_getmethods__["coef0"] = _ml.CvSVMParams_coef0_get
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if _newclass:coef0 = _swig_property(_ml.CvSVMParams_coef0_get, _ml.CvSVMParams_coef0_set)
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__swig_setmethods__["C"] = _ml.CvSVMParams_C_set
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__swig_getmethods__["C"] = _ml.CvSVMParams_C_get
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if _newclass:C = _swig_property(_ml.CvSVMParams_C_get, _ml.CvSVMParams_C_set)
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__swig_setmethods__["nu"] = _ml.CvSVMParams_nu_set
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__swig_getmethods__["nu"] = _ml.CvSVMParams_nu_get
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if _newclass:nu = _swig_property(_ml.CvSVMParams_nu_get, _ml.CvSVMParams_nu_set)
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__swig_setmethods__["p"] = _ml.CvSVMParams_p_set
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|
__swig_getmethods__["p"] = _ml.CvSVMParams_p_get
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|
if _newclass:p = _swig_property(_ml.CvSVMParams_p_get, _ml.CvSVMParams_p_set)
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|
__swig_setmethods__["class_weights"] = _ml.CvSVMParams_class_weights_set
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|
__swig_getmethods__["class_weights"] = _ml.CvSVMParams_class_weights_get
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|
if _newclass:class_weights = _swig_property(_ml.CvSVMParams_class_weights_get, _ml.CvSVMParams_class_weights_set)
|
|
__swig_setmethods__["term_crit"] = _ml.CvSVMParams_term_crit_set
|
|
__swig_getmethods__["term_crit"] = _ml.CvSVMParams_term_crit_get
|
|
if _newclass:term_crit = _swig_property(_ml.CvSVMParams_term_crit_get, _ml.CvSVMParams_term_crit_set)
|
|
__swig_destroy__ = _ml.delete_CvSVMParams
|
|
__del__ = lambda self : None;
|
|
CvSVMParams_swigregister = _ml.CvSVMParams_swigregister
|
|
CvSVMParams_swigregister(CvSVMParams)
|
|
|
|
class CvSVMKernel(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvSVMKernel, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvSVMKernel, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvSVMKernel(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
def create(self, *args): return _ml.CvSVMKernel_create(self, *args)
|
|
__swig_destroy__ = _ml.delete_CvSVMKernel
|
|
__del__ = lambda self : None;
|
|
def clear(self): return _ml.CvSVMKernel_clear(self)
|
|
def calc(self, *args): return _ml.CvSVMKernel_calc(self, *args)
|
|
__swig_setmethods__["params"] = _ml.CvSVMKernel_params_set
|
|
__swig_getmethods__["params"] = _ml.CvSVMKernel_params_get
|
|
if _newclass:params = _swig_property(_ml.CvSVMKernel_params_get, _ml.CvSVMKernel_params_set)
|
|
__swig_setmethods__["calc_func"] = _ml.CvSVMKernel_calc_func_set
|
|
__swig_getmethods__["calc_func"] = _ml.CvSVMKernel_calc_func_get
|
|
if _newclass:calc_func = _swig_property(_ml.CvSVMKernel_calc_func_get, _ml.CvSVMKernel_calc_func_set)
|
|
def calc_non_rbf_base(self, *args): return _ml.CvSVMKernel_calc_non_rbf_base(self, *args)
|
|
def calc_linear(self, *args): return _ml.CvSVMKernel_calc_linear(self, *args)
|
|
def calc_rbf(self, *args): return _ml.CvSVMKernel_calc_rbf(self, *args)
|
|
def calc_poly(self, *args): return _ml.CvSVMKernel_calc_poly(self, *args)
|
|
def calc_sigmoid(self, *args): return _ml.CvSVMKernel_calc_sigmoid(self, *args)
|
|
CvSVMKernel_swigregister = _ml.CvSVMKernel_swigregister
|
|
CvSVMKernel_swigregister(CvSVMKernel)
|
|
|
|
class CvSVMKernelRow(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvSVMKernelRow, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvSVMKernelRow, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["prev"] = _ml.CvSVMKernelRow_prev_set
|
|
__swig_getmethods__["prev"] = _ml.CvSVMKernelRow_prev_get
|
|
if _newclass:prev = _swig_property(_ml.CvSVMKernelRow_prev_get, _ml.CvSVMKernelRow_prev_set)
|
|
__swig_setmethods__["next"] = _ml.CvSVMKernelRow_next_set
|
|
__swig_getmethods__["next"] = _ml.CvSVMKernelRow_next_get
|
|
if _newclass:next = _swig_property(_ml.CvSVMKernelRow_next_get, _ml.CvSVMKernelRow_next_set)
|
|
__swig_setmethods__["data"] = _ml.CvSVMKernelRow_data_set
|
|
__swig_getmethods__["data"] = _ml.CvSVMKernelRow_data_get
|
|
if _newclass:data = _swig_property(_ml.CvSVMKernelRow_data_get, _ml.CvSVMKernelRow_data_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvSVMKernelRow()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvSVMKernelRow
|
|
__del__ = lambda self : None;
|
|
CvSVMKernelRow_swigregister = _ml.CvSVMKernelRow_swigregister
|
|
CvSVMKernelRow_swigregister(CvSVMKernelRow)
|
|
|
|
class CvSVMSolutionInfo(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvSVMSolutionInfo, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvSVMSolutionInfo, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["obj"] = _ml.CvSVMSolutionInfo_obj_set
|
|
__swig_getmethods__["obj"] = _ml.CvSVMSolutionInfo_obj_get
|
|
if _newclass:obj = _swig_property(_ml.CvSVMSolutionInfo_obj_get, _ml.CvSVMSolutionInfo_obj_set)
|
|
__swig_setmethods__["rho"] = _ml.CvSVMSolutionInfo_rho_set
|
|
__swig_getmethods__["rho"] = _ml.CvSVMSolutionInfo_rho_get
|
|
if _newclass:rho = _swig_property(_ml.CvSVMSolutionInfo_rho_get, _ml.CvSVMSolutionInfo_rho_set)
|
|
__swig_setmethods__["upper_bound_p"] = _ml.CvSVMSolutionInfo_upper_bound_p_set
|
|
__swig_getmethods__["upper_bound_p"] = _ml.CvSVMSolutionInfo_upper_bound_p_get
|
|
if _newclass:upper_bound_p = _swig_property(_ml.CvSVMSolutionInfo_upper_bound_p_get, _ml.CvSVMSolutionInfo_upper_bound_p_set)
|
|
__swig_setmethods__["upper_bound_n"] = _ml.CvSVMSolutionInfo_upper_bound_n_set
|
|
__swig_getmethods__["upper_bound_n"] = _ml.CvSVMSolutionInfo_upper_bound_n_get
|
|
if _newclass:upper_bound_n = _swig_property(_ml.CvSVMSolutionInfo_upper_bound_n_get, _ml.CvSVMSolutionInfo_upper_bound_n_set)
|
|
__swig_setmethods__["r"] = _ml.CvSVMSolutionInfo_r_set
|
|
__swig_getmethods__["r"] = _ml.CvSVMSolutionInfo_r_get
|
|
if _newclass:r = _swig_property(_ml.CvSVMSolutionInfo_r_get, _ml.CvSVMSolutionInfo_r_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvSVMSolutionInfo()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvSVMSolutionInfo
|
|
__del__ = lambda self : None;
|
|
CvSVMSolutionInfo_swigregister = _ml.CvSVMSolutionInfo_swigregister
|
|
CvSVMSolutionInfo_swigregister(CvSVMSolutionInfo)
|
|
|
|
class CvSVMSolver(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvSVMSolver, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvSVMSolver, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvSVMSolver(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
def create(self, *args): return _ml.CvSVMSolver_create(self, *args)
|
|
__swig_destroy__ = _ml.delete_CvSVMSolver
|
|
__del__ = lambda self : None;
|
|
def clear(self): return _ml.CvSVMSolver_clear(self)
|
|
def solve_generic(self, *args): return _ml.CvSVMSolver_solve_generic(self, *args)
|
|
def solve_c_svc(self, *args): return _ml.CvSVMSolver_solve_c_svc(self, *args)
|
|
def solve_nu_svc(self, *args): return _ml.CvSVMSolver_solve_nu_svc(self, *args)
|
|
def solve_one_class(self, *args): return _ml.CvSVMSolver_solve_one_class(self, *args)
|
|
def solve_eps_svr(self, *args): return _ml.CvSVMSolver_solve_eps_svr(self, *args)
|
|
def solve_nu_svr(self, *args): return _ml.CvSVMSolver_solve_nu_svr(self, *args)
|
|
def get_row_base(self, *args): return _ml.CvSVMSolver_get_row_base(self, *args)
|
|
def get_row(self, *args): return _ml.CvSVMSolver_get_row(self, *args)
|
|
__swig_setmethods__["sample_count"] = _ml.CvSVMSolver_sample_count_set
|
|
__swig_getmethods__["sample_count"] = _ml.CvSVMSolver_sample_count_get
|
|
if _newclass:sample_count = _swig_property(_ml.CvSVMSolver_sample_count_get, _ml.CvSVMSolver_sample_count_set)
|
|
__swig_setmethods__["var_count"] = _ml.CvSVMSolver_var_count_set
|
|
__swig_getmethods__["var_count"] = _ml.CvSVMSolver_var_count_get
|
|
if _newclass:var_count = _swig_property(_ml.CvSVMSolver_var_count_get, _ml.CvSVMSolver_var_count_set)
|
|
__swig_setmethods__["cache_size"] = _ml.CvSVMSolver_cache_size_set
|
|
__swig_getmethods__["cache_size"] = _ml.CvSVMSolver_cache_size_get
|
|
if _newclass:cache_size = _swig_property(_ml.CvSVMSolver_cache_size_get, _ml.CvSVMSolver_cache_size_set)
|
|
__swig_setmethods__["cache_line_size"] = _ml.CvSVMSolver_cache_line_size_set
|
|
__swig_getmethods__["cache_line_size"] = _ml.CvSVMSolver_cache_line_size_get
|
|
if _newclass:cache_line_size = _swig_property(_ml.CvSVMSolver_cache_line_size_get, _ml.CvSVMSolver_cache_line_size_set)
|
|
__swig_setmethods__["samples"] = _ml.CvSVMSolver_samples_set
|
|
__swig_getmethods__["samples"] = _ml.CvSVMSolver_samples_get
|
|
if _newclass:samples = _swig_property(_ml.CvSVMSolver_samples_get, _ml.CvSVMSolver_samples_set)
|
|
__swig_setmethods__["params"] = _ml.CvSVMSolver_params_set
|
|
__swig_getmethods__["params"] = _ml.CvSVMSolver_params_get
|
|
if _newclass:params = _swig_property(_ml.CvSVMSolver_params_get, _ml.CvSVMSolver_params_set)
|
|
__swig_setmethods__["storage"] = _ml.CvSVMSolver_storage_set
|
|
__swig_getmethods__["storage"] = _ml.CvSVMSolver_storage_get
|
|
if _newclass:storage = _swig_property(_ml.CvSVMSolver_storage_get, _ml.CvSVMSolver_storage_set)
|
|
__swig_setmethods__["lru_list"] = _ml.CvSVMSolver_lru_list_set
|
|
__swig_getmethods__["lru_list"] = _ml.CvSVMSolver_lru_list_get
|
|
if _newclass:lru_list = _swig_property(_ml.CvSVMSolver_lru_list_get, _ml.CvSVMSolver_lru_list_set)
|
|
__swig_setmethods__["rows"] = _ml.CvSVMSolver_rows_set
|
|
__swig_getmethods__["rows"] = _ml.CvSVMSolver_rows_get
|
|
if _newclass:rows = _swig_property(_ml.CvSVMSolver_rows_get, _ml.CvSVMSolver_rows_set)
|
|
__swig_setmethods__["alpha_count"] = _ml.CvSVMSolver_alpha_count_set
|
|
__swig_getmethods__["alpha_count"] = _ml.CvSVMSolver_alpha_count_get
|
|
if _newclass:alpha_count = _swig_property(_ml.CvSVMSolver_alpha_count_get, _ml.CvSVMSolver_alpha_count_set)
|
|
__swig_setmethods__["G"] = _ml.CvSVMSolver_G_set
|
|
__swig_getmethods__["G"] = _ml.CvSVMSolver_G_get
|
|
if _newclass:G = _swig_property(_ml.CvSVMSolver_G_get, _ml.CvSVMSolver_G_set)
|
|
__swig_setmethods__["alpha"] = _ml.CvSVMSolver_alpha_set
|
|
__swig_getmethods__["alpha"] = _ml.CvSVMSolver_alpha_get
|
|
if _newclass:alpha = _swig_property(_ml.CvSVMSolver_alpha_get, _ml.CvSVMSolver_alpha_set)
|
|
__swig_setmethods__["alpha_status"] = _ml.CvSVMSolver_alpha_status_set
|
|
__swig_getmethods__["alpha_status"] = _ml.CvSVMSolver_alpha_status_get
|
|
if _newclass:alpha_status = _swig_property(_ml.CvSVMSolver_alpha_status_get, _ml.CvSVMSolver_alpha_status_set)
|
|
__swig_setmethods__["y"] = _ml.CvSVMSolver_y_set
|
|
__swig_getmethods__["y"] = _ml.CvSVMSolver_y_get
|
|
if _newclass:y = _swig_property(_ml.CvSVMSolver_y_get, _ml.CvSVMSolver_y_set)
|
|
__swig_setmethods__["b"] = _ml.CvSVMSolver_b_set
|
|
__swig_getmethods__["b"] = _ml.CvSVMSolver_b_get
|
|
if _newclass:b = _swig_property(_ml.CvSVMSolver_b_get, _ml.CvSVMSolver_b_set)
|
|
__swig_setmethods__["buf"] = _ml.CvSVMSolver_buf_set
|
|
__swig_getmethods__["buf"] = _ml.CvSVMSolver_buf_get
|
|
if _newclass:buf = _swig_property(_ml.CvSVMSolver_buf_get, _ml.CvSVMSolver_buf_set)
|
|
__swig_setmethods__["eps"] = _ml.CvSVMSolver_eps_set
|
|
__swig_getmethods__["eps"] = _ml.CvSVMSolver_eps_get
|
|
if _newclass:eps = _swig_property(_ml.CvSVMSolver_eps_get, _ml.CvSVMSolver_eps_set)
|
|
__swig_setmethods__["max_iter"] = _ml.CvSVMSolver_max_iter_set
|
|
__swig_getmethods__["max_iter"] = _ml.CvSVMSolver_max_iter_get
|
|
if _newclass:max_iter = _swig_property(_ml.CvSVMSolver_max_iter_get, _ml.CvSVMSolver_max_iter_set)
|
|
__swig_setmethods__["C"] = _ml.CvSVMSolver_C_set
|
|
__swig_getmethods__["C"] = _ml.CvSVMSolver_C_get
|
|
if _newclass:C = _swig_property(_ml.CvSVMSolver_C_get, _ml.CvSVMSolver_C_set)
|
|
__swig_setmethods__["kernel"] = _ml.CvSVMSolver_kernel_set
|
|
__swig_getmethods__["kernel"] = _ml.CvSVMSolver_kernel_get
|
|
if _newclass:kernel = _swig_property(_ml.CvSVMSolver_kernel_get, _ml.CvSVMSolver_kernel_set)
|
|
__swig_setmethods__["select_working_set_func"] = _ml.CvSVMSolver_select_working_set_func_set
|
|
__swig_getmethods__["select_working_set_func"] = _ml.CvSVMSolver_select_working_set_func_get
|
|
if _newclass:select_working_set_func = _swig_property(_ml.CvSVMSolver_select_working_set_func_get, _ml.CvSVMSolver_select_working_set_func_set)
|
|
__swig_setmethods__["calc_rho_func"] = _ml.CvSVMSolver_calc_rho_func_set
|
|
__swig_getmethods__["calc_rho_func"] = _ml.CvSVMSolver_calc_rho_func_get
|
|
if _newclass:calc_rho_func = _swig_property(_ml.CvSVMSolver_calc_rho_func_get, _ml.CvSVMSolver_calc_rho_func_set)
|
|
__swig_setmethods__["get_row_func"] = _ml.CvSVMSolver_get_row_func_set
|
|
__swig_getmethods__["get_row_func"] = _ml.CvSVMSolver_get_row_func_get
|
|
if _newclass:get_row_func = _swig_property(_ml.CvSVMSolver_get_row_func_get, _ml.CvSVMSolver_get_row_func_set)
|
|
def select_working_set(self, *args): return _ml.CvSVMSolver_select_working_set(self, *args)
|
|
def select_working_set_nu_svm(self, *args): return _ml.CvSVMSolver_select_working_set_nu_svm(self, *args)
|
|
def calc_rho(self, *args): return _ml.CvSVMSolver_calc_rho(self, *args)
|
|
def calc_rho_nu_svm(self, *args): return _ml.CvSVMSolver_calc_rho_nu_svm(self, *args)
|
|
def get_row_svc(self, *args): return _ml.CvSVMSolver_get_row_svc(self, *args)
|
|
def get_row_one_class(self, *args): return _ml.CvSVMSolver_get_row_one_class(self, *args)
|
|
def get_row_svr(self, *args): return _ml.CvSVMSolver_get_row_svr(self, *args)
|
|
CvSVMSolver_swigregister = _ml.CvSVMSolver_swigregister
|
|
CvSVMSolver_swigregister(CvSVMSolver)
|
|
|
|
class CvSVMDecisionFunc(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvSVMDecisionFunc, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvSVMDecisionFunc, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["rho"] = _ml.CvSVMDecisionFunc_rho_set
|
|
__swig_getmethods__["rho"] = _ml.CvSVMDecisionFunc_rho_get
|
|
if _newclass:rho = _swig_property(_ml.CvSVMDecisionFunc_rho_get, _ml.CvSVMDecisionFunc_rho_set)
|
|
__swig_setmethods__["sv_count"] = _ml.CvSVMDecisionFunc_sv_count_set
|
|
__swig_getmethods__["sv_count"] = _ml.CvSVMDecisionFunc_sv_count_get
|
|
if _newclass:sv_count = _swig_property(_ml.CvSVMDecisionFunc_sv_count_get, _ml.CvSVMDecisionFunc_sv_count_set)
|
|
__swig_setmethods__["alpha"] = _ml.CvSVMDecisionFunc_alpha_set
|
|
__swig_getmethods__["alpha"] = _ml.CvSVMDecisionFunc_alpha_get
|
|
if _newclass:alpha = _swig_property(_ml.CvSVMDecisionFunc_alpha_get, _ml.CvSVMDecisionFunc_alpha_set)
|
|
__swig_setmethods__["sv_index"] = _ml.CvSVMDecisionFunc_sv_index_set
|
|
__swig_getmethods__["sv_index"] = _ml.CvSVMDecisionFunc_sv_index_get
|
|
if _newclass:sv_index = _swig_property(_ml.CvSVMDecisionFunc_sv_index_get, _ml.CvSVMDecisionFunc_sv_index_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvSVMDecisionFunc()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvSVMDecisionFunc
|
|
__del__ = lambda self : None;
|
|
CvSVMDecisionFunc_swigregister = _ml.CvSVMDecisionFunc_swigregister
|
|
CvSVMDecisionFunc_swigregister(CvSVMDecisionFunc)
|
|
|
|
class CvSVM(CvStatModel):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvSVM, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvSVM, name)
|
|
__repr__ = _swig_repr
|
|
C_SVC = _ml.CvSVM_C_SVC
|
|
NU_SVC = _ml.CvSVM_NU_SVC
|
|
ONE_CLASS = _ml.CvSVM_ONE_CLASS
|
|
EPS_SVR = _ml.CvSVM_EPS_SVR
|
|
NU_SVR = _ml.CvSVM_NU_SVR
|
|
LINEAR = _ml.CvSVM_LINEAR
|
|
POLY = _ml.CvSVM_POLY
|
|
RBF = _ml.CvSVM_RBF
|
|
SIGMOID = _ml.CvSVM_SIGMOID
|
|
C = _ml.CvSVM_C
|
|
GAMMA = _ml.CvSVM_GAMMA
|
|
P = _ml.CvSVM_P
|
|
NU = _ml.CvSVM_NU
|
|
COEF = _ml.CvSVM_COEF
|
|
DEGREE = _ml.CvSVM_DEGREE
|
|
__swig_destroy__ = _ml.delete_CvSVM
|
|
__del__ = lambda self : None;
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvSVM(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
def train(self, *args): return _ml.CvSVM_train(self, *args)
|
|
def train_auto(self, *args): return _ml.CvSVM_train_auto(self, *args)
|
|
def predict(self, *args): return _ml.CvSVM_predict(self, *args)
|
|
def get_support_vector_count(self): return _ml.CvSVM_get_support_vector_count(self)
|
|
def get_support_vector(self, *args): return _ml.CvSVM_get_support_vector(self, *args)
|
|
def get_params(self): return _ml.CvSVM_get_params(self)
|
|
def clear(self): return _ml.CvSVM_clear(self)
|
|
__swig_getmethods__["get_default_grid"] = lambda x: _ml.CvSVM_get_default_grid
|
|
if _newclass:get_default_grid = staticmethod(_ml.CvSVM_get_default_grid)
|
|
def write(self, *args): return _ml.CvSVM_write(self, *args)
|
|
def read(self, *args): return _ml.CvSVM_read(self, *args)
|
|
def get_var_count(self): return _ml.CvSVM_get_var_count(self)
|
|
CvSVM_swigregister = _ml.CvSVM_swigregister
|
|
CvSVM_swigregister(CvSVM)
|
|
|
|
def CvSVM_get_default_grid(*args):
|
|
return _ml.CvSVM_get_default_grid(*args)
|
|
CvSVM_get_default_grid = _ml.CvSVM_get_default_grid
|
|
|
|
class CvEMParams(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvEMParams, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvEMParams, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvEMParams(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_setmethods__["nclusters"] = _ml.CvEMParams_nclusters_set
|
|
__swig_getmethods__["nclusters"] = _ml.CvEMParams_nclusters_get
|
|
if _newclass:nclusters = _swig_property(_ml.CvEMParams_nclusters_get, _ml.CvEMParams_nclusters_set)
|
|
__swig_setmethods__["cov_mat_type"] = _ml.CvEMParams_cov_mat_type_set
|
|
__swig_getmethods__["cov_mat_type"] = _ml.CvEMParams_cov_mat_type_get
|
|
if _newclass:cov_mat_type = _swig_property(_ml.CvEMParams_cov_mat_type_get, _ml.CvEMParams_cov_mat_type_set)
|
|
__swig_setmethods__["start_step"] = _ml.CvEMParams_start_step_set
|
|
__swig_getmethods__["start_step"] = _ml.CvEMParams_start_step_get
|
|
if _newclass:start_step = _swig_property(_ml.CvEMParams_start_step_get, _ml.CvEMParams_start_step_set)
|
|
__swig_setmethods__["probs"] = _ml.CvEMParams_probs_set
|
|
__swig_getmethods__["probs"] = _ml.CvEMParams_probs_get
|
|
if _newclass:probs = _swig_property(_ml.CvEMParams_probs_get, _ml.CvEMParams_probs_set)
|
|
__swig_setmethods__["weights"] = _ml.CvEMParams_weights_set
|
|
__swig_getmethods__["weights"] = _ml.CvEMParams_weights_get
|
|
if _newclass:weights = _swig_property(_ml.CvEMParams_weights_get, _ml.CvEMParams_weights_set)
|
|
__swig_setmethods__["means"] = _ml.CvEMParams_means_set
|
|
__swig_getmethods__["means"] = _ml.CvEMParams_means_get
|
|
if _newclass:means = _swig_property(_ml.CvEMParams_means_get, _ml.CvEMParams_means_set)
|
|
__swig_setmethods__["covs"] = _ml.CvEMParams_covs_set
|
|
__swig_getmethods__["covs"] = _ml.CvEMParams_covs_get
|
|
if _newclass:covs = _swig_property(_ml.CvEMParams_covs_get, _ml.CvEMParams_covs_set)
|
|
__swig_setmethods__["term_crit"] = _ml.CvEMParams_term_crit_set
|
|
__swig_getmethods__["term_crit"] = _ml.CvEMParams_term_crit_get
|
|
if _newclass:term_crit = _swig_property(_ml.CvEMParams_term_crit_get, _ml.CvEMParams_term_crit_set)
|
|
__swig_destroy__ = _ml.delete_CvEMParams
|
|
__del__ = lambda self : None;
|
|
CvEMParams_swigregister = _ml.CvEMParams_swigregister
|
|
CvEMParams_swigregister(CvEMParams)
|
|
|
|
class CvEM(CvStatModel):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvEM, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvEM, name)
|
|
__repr__ = _swig_repr
|
|
COV_MAT_SPHERICAL = _ml.CvEM_COV_MAT_SPHERICAL
|
|
COV_MAT_DIAGONAL = _ml.CvEM_COV_MAT_DIAGONAL
|
|
COV_MAT_GENERIC = _ml.CvEM_COV_MAT_GENERIC
|
|
START_E_STEP = _ml.CvEM_START_E_STEP
|
|
START_M_STEP = _ml.CvEM_START_M_STEP
|
|
START_AUTO_STEP = _ml.CvEM_START_AUTO_STEP
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvEM(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvEM
|
|
__del__ = lambda self : None;
|
|
def train(self, *args): return _ml.CvEM_train(self, *args)
|
|
def predict(self, *args): return _ml.CvEM_predict(self, *args)
|
|
def clear(self): return _ml.CvEM_clear(self)
|
|
def get_nclusters(self): return _ml.CvEM_get_nclusters(self)
|
|
def get_means(self): return _ml.CvEM_get_means(self)
|
|
def get_weights(self): return _ml.CvEM_get_weights(self)
|
|
def get_probs(self): return _ml.CvEM_get_probs(self)
|
|
def get_log_likelihood(self): return _ml.CvEM_get_log_likelihood(self)
|
|
def get_covs(self): return _ml.CvEM_get_covs(self)
|
|
CvEM_swigregister = _ml.CvEM_swigregister
|
|
CvEM_swigregister(CvEM)
|
|
|
|
class CvPair16u32s(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvPair16u32s, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvPair16u32s, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["u"] = _ml.CvPair16u32s_u_set
|
|
__swig_getmethods__["u"] = _ml.CvPair16u32s_u_get
|
|
if _newclass:u = _swig_property(_ml.CvPair16u32s_u_get, _ml.CvPair16u32s_u_set)
|
|
__swig_setmethods__["i"] = _ml.CvPair16u32s_i_set
|
|
__swig_getmethods__["i"] = _ml.CvPair16u32s_i_get
|
|
if _newclass:i = _swig_property(_ml.CvPair16u32s_i_get, _ml.CvPair16u32s_i_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvPair16u32s()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvPair16u32s
|
|
__del__ = lambda self : None;
|
|
CvPair16u32s_swigregister = _ml.CvPair16u32s_swigregister
|
|
CvPair16u32s_swigregister(CvPair16u32s)
|
|
|
|
class CvDTreeSplit(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvDTreeSplit, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvDTreeSplit, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["var_idx"] = _ml.CvDTreeSplit_var_idx_set
|
|
__swig_getmethods__["var_idx"] = _ml.CvDTreeSplit_var_idx_get
|
|
if _newclass:var_idx = _swig_property(_ml.CvDTreeSplit_var_idx_get, _ml.CvDTreeSplit_var_idx_set)
|
|
__swig_setmethods__["condensed_idx"] = _ml.CvDTreeSplit_condensed_idx_set
|
|
__swig_getmethods__["condensed_idx"] = _ml.CvDTreeSplit_condensed_idx_get
|
|
if _newclass:condensed_idx = _swig_property(_ml.CvDTreeSplit_condensed_idx_get, _ml.CvDTreeSplit_condensed_idx_set)
|
|
__swig_setmethods__["inversed"] = _ml.CvDTreeSplit_inversed_set
|
|
__swig_getmethods__["inversed"] = _ml.CvDTreeSplit_inversed_get
|
|
if _newclass:inversed = _swig_property(_ml.CvDTreeSplit_inversed_get, _ml.CvDTreeSplit_inversed_set)
|
|
__swig_setmethods__["quality"] = _ml.CvDTreeSplit_quality_set
|
|
__swig_getmethods__["quality"] = _ml.CvDTreeSplit_quality_get
|
|
if _newclass:quality = _swig_property(_ml.CvDTreeSplit_quality_get, _ml.CvDTreeSplit_quality_set)
|
|
__swig_setmethods__["next"] = _ml.CvDTreeSplit_next_set
|
|
__swig_getmethods__["next"] = _ml.CvDTreeSplit_next_get
|
|
if _newclass:next = _swig_property(_ml.CvDTreeSplit_next_get, _ml.CvDTreeSplit_next_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvDTreeSplit()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvDTreeSplit
|
|
__del__ = lambda self : None;
|
|
CvDTreeSplit_swigregister = _ml.CvDTreeSplit_swigregister
|
|
CvDTreeSplit_swigregister(CvDTreeSplit)
|
|
|
|
class CvDTreeNode(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvDTreeNode, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvDTreeNode, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["class_idx"] = _ml.CvDTreeNode_class_idx_set
|
|
__swig_getmethods__["class_idx"] = _ml.CvDTreeNode_class_idx_get
|
|
if _newclass:class_idx = _swig_property(_ml.CvDTreeNode_class_idx_get, _ml.CvDTreeNode_class_idx_set)
|
|
__swig_setmethods__["Tn"] = _ml.CvDTreeNode_Tn_set
|
|
__swig_getmethods__["Tn"] = _ml.CvDTreeNode_Tn_get
|
|
if _newclass:Tn = _swig_property(_ml.CvDTreeNode_Tn_get, _ml.CvDTreeNode_Tn_set)
|
|
__swig_setmethods__["value"] = _ml.CvDTreeNode_value_set
|
|
__swig_getmethods__["value"] = _ml.CvDTreeNode_value_get
|
|
if _newclass:value = _swig_property(_ml.CvDTreeNode_value_get, _ml.CvDTreeNode_value_set)
|
|
__swig_setmethods__["parent"] = _ml.CvDTreeNode_parent_set
|
|
__swig_getmethods__["parent"] = _ml.CvDTreeNode_parent_get
|
|
if _newclass:parent = _swig_property(_ml.CvDTreeNode_parent_get, _ml.CvDTreeNode_parent_set)
|
|
__swig_setmethods__["left"] = _ml.CvDTreeNode_left_set
|
|
__swig_getmethods__["left"] = _ml.CvDTreeNode_left_get
|
|
if _newclass:left = _swig_property(_ml.CvDTreeNode_left_get, _ml.CvDTreeNode_left_set)
|
|
__swig_setmethods__["right"] = _ml.CvDTreeNode_right_set
|
|
__swig_getmethods__["right"] = _ml.CvDTreeNode_right_get
|
|
if _newclass:right = _swig_property(_ml.CvDTreeNode_right_get, _ml.CvDTreeNode_right_set)
|
|
__swig_setmethods__["split"] = _ml.CvDTreeNode_split_set
|
|
__swig_getmethods__["split"] = _ml.CvDTreeNode_split_get
|
|
if _newclass:split = _swig_property(_ml.CvDTreeNode_split_get, _ml.CvDTreeNode_split_set)
|
|
__swig_setmethods__["sample_count"] = _ml.CvDTreeNode_sample_count_set
|
|
__swig_getmethods__["sample_count"] = _ml.CvDTreeNode_sample_count_get
|
|
if _newclass:sample_count = _swig_property(_ml.CvDTreeNode_sample_count_get, _ml.CvDTreeNode_sample_count_set)
|
|
__swig_setmethods__["depth"] = _ml.CvDTreeNode_depth_set
|
|
__swig_getmethods__["depth"] = _ml.CvDTreeNode_depth_get
|
|
if _newclass:depth = _swig_property(_ml.CvDTreeNode_depth_get, _ml.CvDTreeNode_depth_set)
|
|
__swig_setmethods__["num_valid"] = _ml.CvDTreeNode_num_valid_set
|
|
__swig_getmethods__["num_valid"] = _ml.CvDTreeNode_num_valid_get
|
|
if _newclass:num_valid = _swig_property(_ml.CvDTreeNode_num_valid_get, _ml.CvDTreeNode_num_valid_set)
|
|
__swig_setmethods__["offset"] = _ml.CvDTreeNode_offset_set
|
|
__swig_getmethods__["offset"] = _ml.CvDTreeNode_offset_get
|
|
if _newclass:offset = _swig_property(_ml.CvDTreeNode_offset_get, _ml.CvDTreeNode_offset_set)
|
|
__swig_setmethods__["buf_idx"] = _ml.CvDTreeNode_buf_idx_set
|
|
__swig_getmethods__["buf_idx"] = _ml.CvDTreeNode_buf_idx_get
|
|
if _newclass:buf_idx = _swig_property(_ml.CvDTreeNode_buf_idx_get, _ml.CvDTreeNode_buf_idx_set)
|
|
__swig_setmethods__["maxlr"] = _ml.CvDTreeNode_maxlr_set
|
|
__swig_getmethods__["maxlr"] = _ml.CvDTreeNode_maxlr_get
|
|
if _newclass:maxlr = _swig_property(_ml.CvDTreeNode_maxlr_get, _ml.CvDTreeNode_maxlr_set)
|
|
__swig_setmethods__["complexity"] = _ml.CvDTreeNode_complexity_set
|
|
__swig_getmethods__["complexity"] = _ml.CvDTreeNode_complexity_get
|
|
if _newclass:complexity = _swig_property(_ml.CvDTreeNode_complexity_get, _ml.CvDTreeNode_complexity_set)
|
|
__swig_setmethods__["alpha"] = _ml.CvDTreeNode_alpha_set
|
|
__swig_getmethods__["alpha"] = _ml.CvDTreeNode_alpha_get
|
|
if _newclass:alpha = _swig_property(_ml.CvDTreeNode_alpha_get, _ml.CvDTreeNode_alpha_set)
|
|
__swig_setmethods__["node_risk"] = _ml.CvDTreeNode_node_risk_set
|
|
__swig_getmethods__["node_risk"] = _ml.CvDTreeNode_node_risk_get
|
|
if _newclass:node_risk = _swig_property(_ml.CvDTreeNode_node_risk_get, _ml.CvDTreeNode_node_risk_set)
|
|
__swig_setmethods__["tree_risk"] = _ml.CvDTreeNode_tree_risk_set
|
|
__swig_getmethods__["tree_risk"] = _ml.CvDTreeNode_tree_risk_get
|
|
if _newclass:tree_risk = _swig_property(_ml.CvDTreeNode_tree_risk_get, _ml.CvDTreeNode_tree_risk_set)
|
|
__swig_setmethods__["tree_error"] = _ml.CvDTreeNode_tree_error_set
|
|
__swig_getmethods__["tree_error"] = _ml.CvDTreeNode_tree_error_get
|
|
if _newclass:tree_error = _swig_property(_ml.CvDTreeNode_tree_error_get, _ml.CvDTreeNode_tree_error_set)
|
|
__swig_setmethods__["cv_Tn"] = _ml.CvDTreeNode_cv_Tn_set
|
|
__swig_getmethods__["cv_Tn"] = _ml.CvDTreeNode_cv_Tn_get
|
|
if _newclass:cv_Tn = _swig_property(_ml.CvDTreeNode_cv_Tn_get, _ml.CvDTreeNode_cv_Tn_set)
|
|
__swig_setmethods__["cv_node_risk"] = _ml.CvDTreeNode_cv_node_risk_set
|
|
__swig_getmethods__["cv_node_risk"] = _ml.CvDTreeNode_cv_node_risk_get
|
|
if _newclass:cv_node_risk = _swig_property(_ml.CvDTreeNode_cv_node_risk_get, _ml.CvDTreeNode_cv_node_risk_set)
|
|
__swig_setmethods__["cv_node_error"] = _ml.CvDTreeNode_cv_node_error_set
|
|
__swig_getmethods__["cv_node_error"] = _ml.CvDTreeNode_cv_node_error_get
|
|
if _newclass:cv_node_error = _swig_property(_ml.CvDTreeNode_cv_node_error_get, _ml.CvDTreeNode_cv_node_error_set)
|
|
def get_num_valid(self, *args): return _ml.CvDTreeNode_get_num_valid(self, *args)
|
|
def set_num_valid(self, *args): return _ml.CvDTreeNode_set_num_valid(self, *args)
|
|
def __init__(self):
|
|
this = _ml.new_CvDTreeNode()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvDTreeNode
|
|
__del__ = lambda self : None;
|
|
CvDTreeNode_swigregister = _ml.CvDTreeNode_swigregister
|
|
CvDTreeNode_swigregister(CvDTreeNode)
|
|
|
|
class CvDTreeParams(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvDTreeParams, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvDTreeParams, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["max_categories"] = _ml.CvDTreeParams_max_categories_set
|
|
__swig_getmethods__["max_categories"] = _ml.CvDTreeParams_max_categories_get
|
|
if _newclass:max_categories = _swig_property(_ml.CvDTreeParams_max_categories_get, _ml.CvDTreeParams_max_categories_set)
|
|
__swig_setmethods__["max_depth"] = _ml.CvDTreeParams_max_depth_set
|
|
__swig_getmethods__["max_depth"] = _ml.CvDTreeParams_max_depth_get
|
|
if _newclass:max_depth = _swig_property(_ml.CvDTreeParams_max_depth_get, _ml.CvDTreeParams_max_depth_set)
|
|
__swig_setmethods__["min_sample_count"] = _ml.CvDTreeParams_min_sample_count_set
|
|
__swig_getmethods__["min_sample_count"] = _ml.CvDTreeParams_min_sample_count_get
|
|
if _newclass:min_sample_count = _swig_property(_ml.CvDTreeParams_min_sample_count_get, _ml.CvDTreeParams_min_sample_count_set)
|
|
__swig_setmethods__["cv_folds"] = _ml.CvDTreeParams_cv_folds_set
|
|
__swig_getmethods__["cv_folds"] = _ml.CvDTreeParams_cv_folds_get
|
|
if _newclass:cv_folds = _swig_property(_ml.CvDTreeParams_cv_folds_get, _ml.CvDTreeParams_cv_folds_set)
|
|
__swig_setmethods__["use_surrogates"] = _ml.CvDTreeParams_use_surrogates_set
|
|
__swig_getmethods__["use_surrogates"] = _ml.CvDTreeParams_use_surrogates_get
|
|
if _newclass:use_surrogates = _swig_property(_ml.CvDTreeParams_use_surrogates_get, _ml.CvDTreeParams_use_surrogates_set)
|
|
__swig_setmethods__["use_1se_rule"] = _ml.CvDTreeParams_use_1se_rule_set
|
|
__swig_getmethods__["use_1se_rule"] = _ml.CvDTreeParams_use_1se_rule_get
|
|
if _newclass:use_1se_rule = _swig_property(_ml.CvDTreeParams_use_1se_rule_get, _ml.CvDTreeParams_use_1se_rule_set)
|
|
__swig_setmethods__["truncate_pruned_tree"] = _ml.CvDTreeParams_truncate_pruned_tree_set
|
|
__swig_getmethods__["truncate_pruned_tree"] = _ml.CvDTreeParams_truncate_pruned_tree_get
|
|
if _newclass:truncate_pruned_tree = _swig_property(_ml.CvDTreeParams_truncate_pruned_tree_get, _ml.CvDTreeParams_truncate_pruned_tree_set)
|
|
__swig_setmethods__["regression_accuracy"] = _ml.CvDTreeParams_regression_accuracy_set
|
|
__swig_getmethods__["regression_accuracy"] = _ml.CvDTreeParams_regression_accuracy_get
|
|
if _newclass:regression_accuracy = _swig_property(_ml.CvDTreeParams_regression_accuracy_get, _ml.CvDTreeParams_regression_accuracy_set)
|
|
__swig_setmethods__["priors"] = _ml.CvDTreeParams_priors_set
|
|
__swig_getmethods__["priors"] = _ml.CvDTreeParams_priors_get
|
|
if _newclass:priors = _swig_property(_ml.CvDTreeParams_priors_get, _ml.CvDTreeParams_priors_set)
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvDTreeParams(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvDTreeParams
|
|
__del__ = lambda self : None;
|
|
CvDTreeParams_swigregister = _ml.CvDTreeParams_swigregister
|
|
CvDTreeParams_swigregister(CvDTreeParams)
|
|
|
|
class CvDTreeTrainData(_object):
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__swig_setmethods__ = {}
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__setattr__ = lambda self, name, value: _swig_setattr(self, CvDTreeTrainData, name, value)
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__swig_getmethods__ = {}
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__getattr__ = lambda self, name: _swig_getattr(self, CvDTreeTrainData, name)
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__repr__ = _swig_repr
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def __init__(self, *args):
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this = _ml.new_CvDTreeTrainData(*args)
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try: self.this.append(this)
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except: self.this = this
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__swig_destroy__ = _ml.delete_CvDTreeTrainData
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__del__ = lambda self : None;
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def set_data(self, *args): return _ml.CvDTreeTrainData_set_data(self, *args)
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def do_responses_copy(self): return _ml.CvDTreeTrainData_do_responses_copy(self)
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def get_vectors(self, *args): return _ml.CvDTreeTrainData_get_vectors(self, *args)
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def subsample_data(self, *args): return _ml.CvDTreeTrainData_subsample_data(self, *args)
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def write_params(self, *args): return _ml.CvDTreeTrainData_write_params(self, *args)
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def read_params(self, *args): return _ml.CvDTreeTrainData_read_params(self, *args)
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def clear(self): return _ml.CvDTreeTrainData_clear(self)
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def get_num_classes(self): return _ml.CvDTreeTrainData_get_num_classes(self)
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def get_var_type(self, *args): return _ml.CvDTreeTrainData_get_var_type(self, *args)
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def get_work_var_count(self): return _ml.CvDTreeTrainData_get_work_var_count(self)
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def get_ord_responses(self, *args): return _ml.CvDTreeTrainData_get_ord_responses(self, *args)
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def get_class_labels(self, *args): return _ml.CvDTreeTrainData_get_class_labels(self, *args)
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def get_cv_labels(self, *args): return _ml.CvDTreeTrainData_get_cv_labels(self, *args)
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def get_sample_indices(self, *args): return _ml.CvDTreeTrainData_get_sample_indices(self, *args)
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def get_cat_var_data(self, *args): return _ml.CvDTreeTrainData_get_cat_var_data(self, *args)
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def get_ord_var_data(self, *args): return _ml.CvDTreeTrainData_get_ord_var_data(self, *args)
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def get_child_buf_idx(self, *args): return _ml.CvDTreeTrainData_get_child_buf_idx(self, *args)
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def set_params(self, *args): return _ml.CvDTreeTrainData_set_params(self, *args)
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def new_node(self, *args): return _ml.CvDTreeTrainData_new_node(self, *args)
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def new_split_ord(self, *args): return _ml.CvDTreeTrainData_new_split_ord(self, *args)
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def new_split_cat(self, *args): return _ml.CvDTreeTrainData_new_split_cat(self, *args)
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def free_node_data(self, *args): return _ml.CvDTreeTrainData_free_node_data(self, *args)
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def free_train_data(self): return _ml.CvDTreeTrainData_free_train_data(self)
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def free_node(self, *args): return _ml.CvDTreeTrainData_free_node(self, *args)
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def get_pred_float_buf(self): return _ml.CvDTreeTrainData_get_pred_float_buf(self)
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def get_pred_int_buf(self): return _ml.CvDTreeTrainData_get_pred_int_buf(self)
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def get_resp_float_buf(self): return _ml.CvDTreeTrainData_get_resp_float_buf(self)
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def get_resp_int_buf(self): return _ml.CvDTreeTrainData_get_resp_int_buf(self)
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def get_cv_lables_buf(self): return _ml.CvDTreeTrainData_get_cv_lables_buf(self)
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def get_sample_idx_buf(self): return _ml.CvDTreeTrainData_get_sample_idx_buf(self)
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__swig_setmethods__["pred_float_buf"] = _ml.CvDTreeTrainData_pred_float_buf_set
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__swig_getmethods__["pred_float_buf"] = _ml.CvDTreeTrainData_pred_float_buf_get
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if _newclass:pred_float_buf = _swig_property(_ml.CvDTreeTrainData_pred_float_buf_get, _ml.CvDTreeTrainData_pred_float_buf_set)
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__swig_setmethods__["pred_int_buf"] = _ml.CvDTreeTrainData_pred_int_buf_set
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__swig_getmethods__["pred_int_buf"] = _ml.CvDTreeTrainData_pred_int_buf_get
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if _newclass:pred_int_buf = _swig_property(_ml.CvDTreeTrainData_pred_int_buf_get, _ml.CvDTreeTrainData_pred_int_buf_set)
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__swig_setmethods__["resp_float_buf"] = _ml.CvDTreeTrainData_resp_float_buf_set
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__swig_getmethods__["resp_float_buf"] = _ml.CvDTreeTrainData_resp_float_buf_get
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if _newclass:resp_float_buf = _swig_property(_ml.CvDTreeTrainData_resp_float_buf_get, _ml.CvDTreeTrainData_resp_float_buf_set)
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__swig_setmethods__["resp_int_buf"] = _ml.CvDTreeTrainData_resp_int_buf_set
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__swig_getmethods__["resp_int_buf"] = _ml.CvDTreeTrainData_resp_int_buf_get
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if _newclass:resp_int_buf = _swig_property(_ml.CvDTreeTrainData_resp_int_buf_get, _ml.CvDTreeTrainData_resp_int_buf_set)
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__swig_setmethods__["cv_lables_buf"] = _ml.CvDTreeTrainData_cv_lables_buf_set
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__swig_getmethods__["cv_lables_buf"] = _ml.CvDTreeTrainData_cv_lables_buf_get
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if _newclass:cv_lables_buf = _swig_property(_ml.CvDTreeTrainData_cv_lables_buf_get, _ml.CvDTreeTrainData_cv_lables_buf_set)
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__swig_setmethods__["sample_idx_buf"] = _ml.CvDTreeTrainData_sample_idx_buf_set
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__swig_getmethods__["sample_idx_buf"] = _ml.CvDTreeTrainData_sample_idx_buf_get
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if _newclass:sample_idx_buf = _swig_property(_ml.CvDTreeTrainData_sample_idx_buf_get, _ml.CvDTreeTrainData_sample_idx_buf_set)
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__swig_setmethods__["sample_count"] = _ml.CvDTreeTrainData_sample_count_set
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__swig_getmethods__["sample_count"] = _ml.CvDTreeTrainData_sample_count_get
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if _newclass:sample_count = _swig_property(_ml.CvDTreeTrainData_sample_count_get, _ml.CvDTreeTrainData_sample_count_set)
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__swig_setmethods__["var_all"] = _ml.CvDTreeTrainData_var_all_set
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__swig_getmethods__["var_all"] = _ml.CvDTreeTrainData_var_all_get
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if _newclass:var_all = _swig_property(_ml.CvDTreeTrainData_var_all_get, _ml.CvDTreeTrainData_var_all_set)
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__swig_setmethods__["var_count"] = _ml.CvDTreeTrainData_var_count_set
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__swig_getmethods__["var_count"] = _ml.CvDTreeTrainData_var_count_get
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if _newclass:var_count = _swig_property(_ml.CvDTreeTrainData_var_count_get, _ml.CvDTreeTrainData_var_count_set)
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__swig_setmethods__["max_c_count"] = _ml.CvDTreeTrainData_max_c_count_set
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__swig_getmethods__["max_c_count"] = _ml.CvDTreeTrainData_max_c_count_get
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if _newclass:max_c_count = _swig_property(_ml.CvDTreeTrainData_max_c_count_get, _ml.CvDTreeTrainData_max_c_count_set)
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__swig_setmethods__["ord_var_count"] = _ml.CvDTreeTrainData_ord_var_count_set
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__swig_getmethods__["ord_var_count"] = _ml.CvDTreeTrainData_ord_var_count_get
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if _newclass:ord_var_count = _swig_property(_ml.CvDTreeTrainData_ord_var_count_get, _ml.CvDTreeTrainData_ord_var_count_set)
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__swig_setmethods__["cat_var_count"] = _ml.CvDTreeTrainData_cat_var_count_set
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__swig_getmethods__["cat_var_count"] = _ml.CvDTreeTrainData_cat_var_count_get
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if _newclass:cat_var_count = _swig_property(_ml.CvDTreeTrainData_cat_var_count_get, _ml.CvDTreeTrainData_cat_var_count_set)
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__swig_setmethods__["work_var_count"] = _ml.CvDTreeTrainData_work_var_count_set
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__swig_getmethods__["work_var_count"] = _ml.CvDTreeTrainData_work_var_count_get
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if _newclass:work_var_count = _swig_property(_ml.CvDTreeTrainData_work_var_count_get, _ml.CvDTreeTrainData_work_var_count_set)
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__swig_setmethods__["have_labels"] = _ml.CvDTreeTrainData_have_labels_set
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__swig_getmethods__["have_labels"] = _ml.CvDTreeTrainData_have_labels_get
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if _newclass:have_labels = _swig_property(_ml.CvDTreeTrainData_have_labels_get, _ml.CvDTreeTrainData_have_labels_set)
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__swig_setmethods__["have_priors"] = _ml.CvDTreeTrainData_have_priors_set
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__swig_getmethods__["have_priors"] = _ml.CvDTreeTrainData_have_priors_get
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if _newclass:have_priors = _swig_property(_ml.CvDTreeTrainData_have_priors_get, _ml.CvDTreeTrainData_have_priors_set)
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__swig_setmethods__["is_classifier"] = _ml.CvDTreeTrainData_is_classifier_set
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__swig_getmethods__["is_classifier"] = _ml.CvDTreeTrainData_is_classifier_get
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if _newclass:is_classifier = _swig_property(_ml.CvDTreeTrainData_is_classifier_get, _ml.CvDTreeTrainData_is_classifier_set)
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__swig_setmethods__["tflag"] = _ml.CvDTreeTrainData_tflag_set
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__swig_getmethods__["tflag"] = _ml.CvDTreeTrainData_tflag_get
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if _newclass:tflag = _swig_property(_ml.CvDTreeTrainData_tflag_get, _ml.CvDTreeTrainData_tflag_set)
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__swig_setmethods__["train_data"] = _ml.CvDTreeTrainData_train_data_set
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__swig_getmethods__["train_data"] = _ml.CvDTreeTrainData_train_data_get
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if _newclass:train_data = _swig_property(_ml.CvDTreeTrainData_train_data_get, _ml.CvDTreeTrainData_train_data_set)
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__swig_setmethods__["responses"] = _ml.CvDTreeTrainData_responses_set
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__swig_getmethods__["responses"] = _ml.CvDTreeTrainData_responses_get
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if _newclass:responses = _swig_property(_ml.CvDTreeTrainData_responses_get, _ml.CvDTreeTrainData_responses_set)
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__swig_setmethods__["responses_copy"] = _ml.CvDTreeTrainData_responses_copy_set
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__swig_getmethods__["responses_copy"] = _ml.CvDTreeTrainData_responses_copy_get
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if _newclass:responses_copy = _swig_property(_ml.CvDTreeTrainData_responses_copy_get, _ml.CvDTreeTrainData_responses_copy_set)
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__swig_setmethods__["buf_count"] = _ml.CvDTreeTrainData_buf_count_set
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__swig_getmethods__["buf_count"] = _ml.CvDTreeTrainData_buf_count_get
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if _newclass:buf_count = _swig_property(_ml.CvDTreeTrainData_buf_count_get, _ml.CvDTreeTrainData_buf_count_set)
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__swig_setmethods__["buf_size"] = _ml.CvDTreeTrainData_buf_size_set
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__swig_getmethods__["buf_size"] = _ml.CvDTreeTrainData_buf_size_get
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if _newclass:buf_size = _swig_property(_ml.CvDTreeTrainData_buf_size_get, _ml.CvDTreeTrainData_buf_size_set)
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__swig_setmethods__["shared"] = _ml.CvDTreeTrainData_shared_set
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__swig_getmethods__["shared"] = _ml.CvDTreeTrainData_shared_get
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if _newclass:shared = _swig_property(_ml.CvDTreeTrainData_shared_get, _ml.CvDTreeTrainData_shared_set)
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__swig_setmethods__["is_buf_16u"] = _ml.CvDTreeTrainData_is_buf_16u_set
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__swig_getmethods__["is_buf_16u"] = _ml.CvDTreeTrainData_is_buf_16u_get
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if _newclass:is_buf_16u = _swig_property(_ml.CvDTreeTrainData_is_buf_16u_get, _ml.CvDTreeTrainData_is_buf_16u_set)
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__swig_setmethods__["cat_count"] = _ml.CvDTreeTrainData_cat_count_set
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__swig_getmethods__["cat_count"] = _ml.CvDTreeTrainData_cat_count_get
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if _newclass:cat_count = _swig_property(_ml.CvDTreeTrainData_cat_count_get, _ml.CvDTreeTrainData_cat_count_set)
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__swig_setmethods__["cat_ofs"] = _ml.CvDTreeTrainData_cat_ofs_set
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__swig_getmethods__["cat_ofs"] = _ml.CvDTreeTrainData_cat_ofs_get
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if _newclass:cat_ofs = _swig_property(_ml.CvDTreeTrainData_cat_ofs_get, _ml.CvDTreeTrainData_cat_ofs_set)
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__swig_setmethods__["cat_map"] = _ml.CvDTreeTrainData_cat_map_set
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__swig_getmethods__["cat_map"] = _ml.CvDTreeTrainData_cat_map_get
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if _newclass:cat_map = _swig_property(_ml.CvDTreeTrainData_cat_map_get, _ml.CvDTreeTrainData_cat_map_set)
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__swig_setmethods__["counts"] = _ml.CvDTreeTrainData_counts_set
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__swig_getmethods__["counts"] = _ml.CvDTreeTrainData_counts_get
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if _newclass:counts = _swig_property(_ml.CvDTreeTrainData_counts_get, _ml.CvDTreeTrainData_counts_set)
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__swig_setmethods__["buf"] = _ml.CvDTreeTrainData_buf_set
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__swig_getmethods__["buf"] = _ml.CvDTreeTrainData_buf_get
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if _newclass:buf = _swig_property(_ml.CvDTreeTrainData_buf_get, _ml.CvDTreeTrainData_buf_set)
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__swig_setmethods__["direction"] = _ml.CvDTreeTrainData_direction_set
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__swig_getmethods__["direction"] = _ml.CvDTreeTrainData_direction_get
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if _newclass:direction = _swig_property(_ml.CvDTreeTrainData_direction_get, _ml.CvDTreeTrainData_direction_set)
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__swig_setmethods__["split_buf"] = _ml.CvDTreeTrainData_split_buf_set
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__swig_getmethods__["split_buf"] = _ml.CvDTreeTrainData_split_buf_get
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if _newclass:split_buf = _swig_property(_ml.CvDTreeTrainData_split_buf_get, _ml.CvDTreeTrainData_split_buf_set)
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__swig_setmethods__["var_idx"] = _ml.CvDTreeTrainData_var_idx_set
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__swig_getmethods__["var_idx"] = _ml.CvDTreeTrainData_var_idx_get
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if _newclass:var_idx = _swig_property(_ml.CvDTreeTrainData_var_idx_get, _ml.CvDTreeTrainData_var_idx_set)
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__swig_setmethods__["var_type"] = _ml.CvDTreeTrainData_var_type_set
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__swig_getmethods__["var_type"] = _ml.CvDTreeTrainData_var_type_get
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if _newclass:var_type = _swig_property(_ml.CvDTreeTrainData_var_type_get, _ml.CvDTreeTrainData_var_type_set)
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__swig_setmethods__["priors"] = _ml.CvDTreeTrainData_priors_set
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__swig_getmethods__["priors"] = _ml.CvDTreeTrainData_priors_get
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if _newclass:priors = _swig_property(_ml.CvDTreeTrainData_priors_get, _ml.CvDTreeTrainData_priors_set)
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__swig_setmethods__["priors_mult"] = _ml.CvDTreeTrainData_priors_mult_set
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__swig_getmethods__["priors_mult"] = _ml.CvDTreeTrainData_priors_mult_get
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if _newclass:priors_mult = _swig_property(_ml.CvDTreeTrainData_priors_mult_get, _ml.CvDTreeTrainData_priors_mult_set)
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__swig_setmethods__["params"] = _ml.CvDTreeTrainData_params_set
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__swig_getmethods__["params"] = _ml.CvDTreeTrainData_params_get
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if _newclass:params = _swig_property(_ml.CvDTreeTrainData_params_get, _ml.CvDTreeTrainData_params_set)
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__swig_setmethods__["tree_storage"] = _ml.CvDTreeTrainData_tree_storage_set
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__swig_getmethods__["tree_storage"] = _ml.CvDTreeTrainData_tree_storage_get
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if _newclass:tree_storage = _swig_property(_ml.CvDTreeTrainData_tree_storage_get, _ml.CvDTreeTrainData_tree_storage_set)
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__swig_setmethods__["temp_storage"] = _ml.CvDTreeTrainData_temp_storage_set
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__swig_getmethods__["temp_storage"] = _ml.CvDTreeTrainData_temp_storage_get
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if _newclass:temp_storage = _swig_property(_ml.CvDTreeTrainData_temp_storage_get, _ml.CvDTreeTrainData_temp_storage_set)
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__swig_setmethods__["data_root"] = _ml.CvDTreeTrainData_data_root_set
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__swig_getmethods__["data_root"] = _ml.CvDTreeTrainData_data_root_get
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if _newclass:data_root = _swig_property(_ml.CvDTreeTrainData_data_root_get, _ml.CvDTreeTrainData_data_root_set)
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__swig_setmethods__["node_heap"] = _ml.CvDTreeTrainData_node_heap_set
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__swig_getmethods__["node_heap"] = _ml.CvDTreeTrainData_node_heap_get
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if _newclass:node_heap = _swig_property(_ml.CvDTreeTrainData_node_heap_get, _ml.CvDTreeTrainData_node_heap_set)
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__swig_setmethods__["split_heap"] = _ml.CvDTreeTrainData_split_heap_set
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__swig_getmethods__["split_heap"] = _ml.CvDTreeTrainData_split_heap_get
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if _newclass:split_heap = _swig_property(_ml.CvDTreeTrainData_split_heap_get, _ml.CvDTreeTrainData_split_heap_set)
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__swig_setmethods__["cv_heap"] = _ml.CvDTreeTrainData_cv_heap_set
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__swig_getmethods__["cv_heap"] = _ml.CvDTreeTrainData_cv_heap_get
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if _newclass:cv_heap = _swig_property(_ml.CvDTreeTrainData_cv_heap_get, _ml.CvDTreeTrainData_cv_heap_set)
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__swig_setmethods__["nv_heap"] = _ml.CvDTreeTrainData_nv_heap_set
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__swig_getmethods__["nv_heap"] = _ml.CvDTreeTrainData_nv_heap_get
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if _newclass:nv_heap = _swig_property(_ml.CvDTreeTrainData_nv_heap_get, _ml.CvDTreeTrainData_nv_heap_set)
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__swig_setmethods__["rng"] = _ml.CvDTreeTrainData_rng_set
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|
__swig_getmethods__["rng"] = _ml.CvDTreeTrainData_rng_get
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if _newclass:rng = _swig_property(_ml.CvDTreeTrainData_rng_get, _ml.CvDTreeTrainData_rng_set)
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|
CvDTreeTrainData_swigregister = _ml.CvDTreeTrainData_swigregister
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CvDTreeTrainData_swigregister(CvDTreeTrainData)
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|
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class CvDTree(CvStatModel):
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__swig_setmethods__ = {}
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|
for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
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|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvDTree, name, value)
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|
__swig_getmethods__ = {}
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|
for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
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|
__getattr__ = lambda self, name: _swig_getattr(self, CvDTree, name)
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|
__repr__ = _swig_repr
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|
def __init__(self):
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this = _ml.new_CvDTree()
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try: self.this.append(this)
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|
except: self.this = this
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|
__swig_destroy__ = _ml.delete_CvDTree
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|
__del__ = lambda self : None;
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|
def calc_error(self, *args): return _ml.CvDTree_calc_error(self, *args)
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def train(self, *args): return _ml.CvDTree_train(self, *args)
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def predict(self, *args): return _ml.CvDTree_predict(self, *args)
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def get_var_importance(self): return _ml.CvDTree_get_var_importance(self)
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def clear(self): return _ml.CvDTree_clear(self)
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def read(self, *args): return _ml.CvDTree_read(self, *args)
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def write(self, *args): return _ml.CvDTree_write(self, *args)
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def get_root(self): return _ml.CvDTree_get_root(self)
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def get_pruned_tree_idx(self): return _ml.CvDTree_get_pruned_tree_idx(self)
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def get_data(self): return _ml.CvDTree_get_data(self)
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__swig_setmethods__["pruned_tree_idx"] = _ml.CvDTree_pruned_tree_idx_set
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|
__swig_getmethods__["pruned_tree_idx"] = _ml.CvDTree_pruned_tree_idx_get
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if _newclass:pruned_tree_idx = _swig_property(_ml.CvDTree_pruned_tree_idx_get, _ml.CvDTree_pruned_tree_idx_set)
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CvDTree_swigregister = _ml.CvDTree_swigregister
|
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CvDTree_swigregister(CvDTree)
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class CvForestTree(CvDTree):
|
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__swig_setmethods__ = {}
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|
for _s in [CvDTree]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvForestTree, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvDTree]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvForestTree, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self):
|
|
this = _ml.new_CvForestTree()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvForestTree
|
|
__del__ = lambda self : None;
|
|
def get_var_count(self): return _ml.CvForestTree_get_var_count(self)
|
|
def train(self, *args): return _ml.CvForestTree_train(self, *args)
|
|
def read(self, *args): return _ml.CvForestTree_read(self, *args)
|
|
CvForestTree_swigregister = _ml.CvForestTree_swigregister
|
|
CvForestTree_swigregister(CvForestTree)
|
|
|
|
class CvRTParams(CvDTreeParams):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvDTreeParams]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvRTParams, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvDTreeParams]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvRTParams, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["calc_var_importance"] = _ml.CvRTParams_calc_var_importance_set
|
|
__swig_getmethods__["calc_var_importance"] = _ml.CvRTParams_calc_var_importance_get
|
|
if _newclass:calc_var_importance = _swig_property(_ml.CvRTParams_calc_var_importance_get, _ml.CvRTParams_calc_var_importance_set)
|
|
__swig_setmethods__["nactive_vars"] = _ml.CvRTParams_nactive_vars_set
|
|
__swig_getmethods__["nactive_vars"] = _ml.CvRTParams_nactive_vars_get
|
|
if _newclass:nactive_vars = _swig_property(_ml.CvRTParams_nactive_vars_get, _ml.CvRTParams_nactive_vars_set)
|
|
__swig_setmethods__["term_crit"] = _ml.CvRTParams_term_crit_set
|
|
__swig_getmethods__["term_crit"] = _ml.CvRTParams_term_crit_get
|
|
if _newclass:term_crit = _swig_property(_ml.CvRTParams_term_crit_get, _ml.CvRTParams_term_crit_set)
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvRTParams(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvRTParams
|
|
__del__ = lambda self : None;
|
|
CvRTParams_swigregister = _ml.CvRTParams_swigregister
|
|
CvRTParams_swigregister(CvRTParams)
|
|
|
|
class CvRTrees(CvStatModel):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvRTrees, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvRTrees, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self):
|
|
this = _ml.new_CvRTrees()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvRTrees
|
|
__del__ = lambda self : None;
|
|
def train(self, *args): return _ml.CvRTrees_train(self, *args)
|
|
def predict(self, *args): return _ml.CvRTrees_predict(self, *args)
|
|
def predict_prob(self, *args): return _ml.CvRTrees_predict_prob(self, *args)
|
|
def clear(self): return _ml.CvRTrees_clear(self)
|
|
def get_var_importance(self): return _ml.CvRTrees_get_var_importance(self)
|
|
def get_proximity(self, *args): return _ml.CvRTrees_get_proximity(self, *args)
|
|
def calc_error(self, *args): return _ml.CvRTrees_calc_error(self, *args)
|
|
def get_train_error(self): return _ml.CvRTrees_get_train_error(self)
|
|
def read(self, *args): return _ml.CvRTrees_read(self, *args)
|
|
def write(self, *args): return _ml.CvRTrees_write(self, *args)
|
|
def get_active_var_mask(self): return _ml.CvRTrees_get_active_var_mask(self)
|
|
def get_rng(self): return _ml.CvRTrees_get_rng(self)
|
|
def get_tree_count(self): return _ml.CvRTrees_get_tree_count(self)
|
|
def get_tree(self, *args): return _ml.CvRTrees_get_tree(self, *args)
|
|
CvRTrees_swigregister = _ml.CvRTrees_swigregister
|
|
CvRTrees_swigregister(CvRTrees)
|
|
|
|
class CvERTreeTrainData(CvDTreeTrainData):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvDTreeTrainData]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvERTreeTrainData, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvDTreeTrainData]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvERTreeTrainData, name)
|
|
__repr__ = _swig_repr
|
|
def set_data(self, *args): return _ml.CvERTreeTrainData_set_data(self, *args)
|
|
def get_ord_var_data(self, *args): return _ml.CvERTreeTrainData_get_ord_var_data(self, *args)
|
|
def get_sample_indices(self, *args): return _ml.CvERTreeTrainData_get_sample_indices(self, *args)
|
|
def get_cv_labels(self, *args): return _ml.CvERTreeTrainData_get_cv_labels(self, *args)
|
|
def get_cat_var_data(self, *args): return _ml.CvERTreeTrainData_get_cat_var_data(self, *args)
|
|
def get_vectors(self, *args): return _ml.CvERTreeTrainData_get_vectors(self, *args)
|
|
def subsample_data(self, *args): return _ml.CvERTreeTrainData_subsample_data(self, *args)
|
|
__swig_setmethods__["missing_mask"] = _ml.CvERTreeTrainData_missing_mask_set
|
|
__swig_getmethods__["missing_mask"] = _ml.CvERTreeTrainData_missing_mask_get
|
|
if _newclass:missing_mask = _swig_property(_ml.CvERTreeTrainData_missing_mask_get, _ml.CvERTreeTrainData_missing_mask_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvERTreeTrainData()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvERTreeTrainData
|
|
__del__ = lambda self : None;
|
|
CvERTreeTrainData_swigregister = _ml.CvERTreeTrainData_swigregister
|
|
CvERTreeTrainData_swigregister(CvERTreeTrainData)
|
|
|
|
class CvForestERTree(CvForestTree):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvForestTree]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvForestERTree, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvForestTree]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvForestERTree, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self):
|
|
this = _ml.new_CvForestERTree()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvForestERTree
|
|
__del__ = lambda self : None;
|
|
CvForestERTree_swigregister = _ml.CvForestERTree_swigregister
|
|
CvForestERTree_swigregister(CvForestERTree)
|
|
|
|
class CvERTrees(CvRTrees):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvRTrees]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvERTrees, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvRTrees]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvERTrees, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self):
|
|
this = _ml.new_CvERTrees()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvERTrees
|
|
__del__ = lambda self : None;
|
|
def train(self, *args): return _ml.CvERTrees_train(self, *args)
|
|
CvERTrees_swigregister = _ml.CvERTrees_swigregister
|
|
CvERTrees_swigregister(CvERTrees)
|
|
|
|
class CvBoostParams(CvDTreeParams):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvDTreeParams]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvBoostParams, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvDTreeParams]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvBoostParams, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["boost_type"] = _ml.CvBoostParams_boost_type_set
|
|
__swig_getmethods__["boost_type"] = _ml.CvBoostParams_boost_type_get
|
|
if _newclass:boost_type = _swig_property(_ml.CvBoostParams_boost_type_get, _ml.CvBoostParams_boost_type_set)
|
|
__swig_setmethods__["weak_count"] = _ml.CvBoostParams_weak_count_set
|
|
__swig_getmethods__["weak_count"] = _ml.CvBoostParams_weak_count_get
|
|
if _newclass:weak_count = _swig_property(_ml.CvBoostParams_weak_count_get, _ml.CvBoostParams_weak_count_set)
|
|
__swig_setmethods__["split_criteria"] = _ml.CvBoostParams_split_criteria_set
|
|
__swig_getmethods__["split_criteria"] = _ml.CvBoostParams_split_criteria_get
|
|
if _newclass:split_criteria = _swig_property(_ml.CvBoostParams_split_criteria_get, _ml.CvBoostParams_split_criteria_set)
|
|
__swig_setmethods__["weight_trim_rate"] = _ml.CvBoostParams_weight_trim_rate_set
|
|
__swig_getmethods__["weight_trim_rate"] = _ml.CvBoostParams_weight_trim_rate_get
|
|
if _newclass:weight_trim_rate = _swig_property(_ml.CvBoostParams_weight_trim_rate_get, _ml.CvBoostParams_weight_trim_rate_set)
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvBoostParams(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvBoostParams
|
|
__del__ = lambda self : None;
|
|
CvBoostParams_swigregister = _ml.CvBoostParams_swigregister
|
|
CvBoostParams_swigregister(CvBoostParams)
|
|
|
|
class CvBoostTree(CvDTree):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvDTree]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvBoostTree, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvDTree]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvBoostTree, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self):
|
|
this = _ml.new_CvBoostTree()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvBoostTree
|
|
__del__ = lambda self : None;
|
|
def scale(self, *args): return _ml.CvBoostTree_scale(self, *args)
|
|
def clear(self): return _ml.CvBoostTree_clear(self)
|
|
def train(self, *args): return _ml.CvBoostTree_train(self, *args)
|
|
def read(self, *args): return _ml.CvBoostTree_read(self, *args)
|
|
CvBoostTree_swigregister = _ml.CvBoostTree_swigregister
|
|
CvBoostTree_swigregister(CvBoostTree)
|
|
|
|
class CvBoost(CvStatModel):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvBoost, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvBoost, name)
|
|
__repr__ = _swig_repr
|
|
DISCRETE = _ml.CvBoost_DISCRETE
|
|
REAL = _ml.CvBoost_REAL
|
|
LOGIT = _ml.CvBoost_LOGIT
|
|
GENTLE = _ml.CvBoost_GENTLE
|
|
DEFAULT = _ml.CvBoost_DEFAULT
|
|
GINI = _ml.CvBoost_GINI
|
|
MISCLASS = _ml.CvBoost_MISCLASS
|
|
SQERR = _ml.CvBoost_SQERR
|
|
__swig_destroy__ = _ml.delete_CvBoost
|
|
__del__ = lambda self : None;
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvBoost(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
def train(self, *args): return _ml.CvBoost_train(self, *args)
|
|
def predict(self, *args): return _ml.CvBoost_predict(self, *args)
|
|
def calc_error(self, *args): return _ml.CvBoost_calc_error(self, *args)
|
|
def prune(self, *args): return _ml.CvBoost_prune(self, *args)
|
|
def clear(self): return _ml.CvBoost_clear(self)
|
|
def write(self, *args): return _ml.CvBoost_write(self, *args)
|
|
def read(self, *args): return _ml.CvBoost_read(self, *args)
|
|
def get_active_vars(self, absolute_idx = True): return _ml.CvBoost_get_active_vars(self, absolute_idx)
|
|
def get_weak_predictors(self): return _ml.CvBoost_get_weak_predictors(self)
|
|
def get_weights(self): return _ml.CvBoost_get_weights(self)
|
|
def get_subtree_weights(self): return _ml.CvBoost_get_subtree_weights(self)
|
|
def get_weak_response(self): return _ml.CvBoost_get_weak_response(self)
|
|
def get_params(self): return _ml.CvBoost_get_params(self)
|
|
def get_data(self): return _ml.CvBoost_get_data(self)
|
|
CvBoost_swigregister = _ml.CvBoost_swigregister
|
|
CvBoost_swigregister(CvBoost)
|
|
|
|
class CvANN_MLP_TrainParams(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvANN_MLP_TrainParams, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvANN_MLP_TrainParams, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvANN_MLP_TrainParams(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvANN_MLP_TrainParams
|
|
__del__ = lambda self : None;
|
|
BACKPROP = _ml.CvANN_MLP_TrainParams_BACKPROP
|
|
RPROP = _ml.CvANN_MLP_TrainParams_RPROP
|
|
__swig_setmethods__["term_crit"] = _ml.CvANN_MLP_TrainParams_term_crit_set
|
|
__swig_getmethods__["term_crit"] = _ml.CvANN_MLP_TrainParams_term_crit_get
|
|
if _newclass:term_crit = _swig_property(_ml.CvANN_MLP_TrainParams_term_crit_get, _ml.CvANN_MLP_TrainParams_term_crit_set)
|
|
__swig_setmethods__["train_method"] = _ml.CvANN_MLP_TrainParams_train_method_set
|
|
__swig_getmethods__["train_method"] = _ml.CvANN_MLP_TrainParams_train_method_get
|
|
if _newclass:train_method = _swig_property(_ml.CvANN_MLP_TrainParams_train_method_get, _ml.CvANN_MLP_TrainParams_train_method_set)
|
|
__swig_setmethods__["bp_dw_scale"] = _ml.CvANN_MLP_TrainParams_bp_dw_scale_set
|
|
__swig_getmethods__["bp_dw_scale"] = _ml.CvANN_MLP_TrainParams_bp_dw_scale_get
|
|
if _newclass:bp_dw_scale = _swig_property(_ml.CvANN_MLP_TrainParams_bp_dw_scale_get, _ml.CvANN_MLP_TrainParams_bp_dw_scale_set)
|
|
__swig_setmethods__["bp_moment_scale"] = _ml.CvANN_MLP_TrainParams_bp_moment_scale_set
|
|
__swig_getmethods__["bp_moment_scale"] = _ml.CvANN_MLP_TrainParams_bp_moment_scale_get
|
|
if _newclass:bp_moment_scale = _swig_property(_ml.CvANN_MLP_TrainParams_bp_moment_scale_get, _ml.CvANN_MLP_TrainParams_bp_moment_scale_set)
|
|
__swig_setmethods__["rp_dw0"] = _ml.CvANN_MLP_TrainParams_rp_dw0_set
|
|
__swig_getmethods__["rp_dw0"] = _ml.CvANN_MLP_TrainParams_rp_dw0_get
|
|
if _newclass:rp_dw0 = _swig_property(_ml.CvANN_MLP_TrainParams_rp_dw0_get, _ml.CvANN_MLP_TrainParams_rp_dw0_set)
|
|
__swig_setmethods__["rp_dw_plus"] = _ml.CvANN_MLP_TrainParams_rp_dw_plus_set
|
|
__swig_getmethods__["rp_dw_plus"] = _ml.CvANN_MLP_TrainParams_rp_dw_plus_get
|
|
if _newclass:rp_dw_plus = _swig_property(_ml.CvANN_MLP_TrainParams_rp_dw_plus_get, _ml.CvANN_MLP_TrainParams_rp_dw_plus_set)
|
|
__swig_setmethods__["rp_dw_minus"] = _ml.CvANN_MLP_TrainParams_rp_dw_minus_set
|
|
__swig_getmethods__["rp_dw_minus"] = _ml.CvANN_MLP_TrainParams_rp_dw_minus_get
|
|
if _newclass:rp_dw_minus = _swig_property(_ml.CvANN_MLP_TrainParams_rp_dw_minus_get, _ml.CvANN_MLP_TrainParams_rp_dw_minus_set)
|
|
__swig_setmethods__["rp_dw_min"] = _ml.CvANN_MLP_TrainParams_rp_dw_min_set
|
|
__swig_getmethods__["rp_dw_min"] = _ml.CvANN_MLP_TrainParams_rp_dw_min_get
|
|
if _newclass:rp_dw_min = _swig_property(_ml.CvANN_MLP_TrainParams_rp_dw_min_get, _ml.CvANN_MLP_TrainParams_rp_dw_min_set)
|
|
__swig_setmethods__["rp_dw_max"] = _ml.CvANN_MLP_TrainParams_rp_dw_max_set
|
|
__swig_getmethods__["rp_dw_max"] = _ml.CvANN_MLP_TrainParams_rp_dw_max_get
|
|
if _newclass:rp_dw_max = _swig_property(_ml.CvANN_MLP_TrainParams_rp_dw_max_get, _ml.CvANN_MLP_TrainParams_rp_dw_max_set)
|
|
CvANN_MLP_TrainParams_swigregister = _ml.CvANN_MLP_TrainParams_swigregister
|
|
CvANN_MLP_TrainParams_swigregister(CvANN_MLP_TrainParams)
|
|
|
|
class CvANN_MLP(CvStatModel):
|
|
__swig_setmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{}))
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvANN_MLP, name, value)
|
|
__swig_getmethods__ = {}
|
|
for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{}))
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvANN_MLP, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvANN_MLP(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvANN_MLP
|
|
__del__ = lambda self : None;
|
|
def create(self, *args): return _ml.CvANN_MLP_create(self, *args)
|
|
def train(self, *args): return _ml.CvANN_MLP_train(self, *args)
|
|
def predict(self, *args): return _ml.CvANN_MLP_predict(self, *args)
|
|
def clear(self): return _ml.CvANN_MLP_clear(self)
|
|
IDENTITY = _ml.CvANN_MLP_IDENTITY
|
|
SIGMOID_SYM = _ml.CvANN_MLP_SIGMOID_SYM
|
|
GAUSSIAN = _ml.CvANN_MLP_GAUSSIAN
|
|
UPDATE_WEIGHTS = _ml.CvANN_MLP_UPDATE_WEIGHTS
|
|
NO_INPUT_SCALE = _ml.CvANN_MLP_NO_INPUT_SCALE
|
|
NO_OUTPUT_SCALE = _ml.CvANN_MLP_NO_OUTPUT_SCALE
|
|
def read(self, *args): return _ml.CvANN_MLP_read(self, *args)
|
|
def write(self, *args): return _ml.CvANN_MLP_write(self, *args)
|
|
def get_layer_count(self): return _ml.CvANN_MLP_get_layer_count(self)
|
|
def get_layer_sizes(self): return _ml.CvANN_MLP_get_layer_sizes(self)
|
|
def get_weights(self, *args): return _ml.CvANN_MLP_get_weights(self, *args)
|
|
CvANN_MLP_swigregister = _ml.CvANN_MLP_swigregister
|
|
CvANN_MLP_swigregister(CvANN_MLP)
|
|
|
|
|
|
def cvRandMVNormal(*args):
|
|
return _ml.cvRandMVNormal(*args)
|
|
cvRandMVNormal = _ml.cvRandMVNormal
|
|
|
|
def cvRandGaussMixture(*args):
|
|
return _ml.cvRandGaussMixture(*args)
|
|
cvRandGaussMixture = _ml.cvRandGaussMixture
|
|
CV_TS_CONCENTRIC_SPHERES = _ml.CV_TS_CONCENTRIC_SPHERES
|
|
|
|
def cvCreateTestSet(*args):
|
|
return _ml.cvCreateTestSet(*args)
|
|
cvCreateTestSet = _ml.cvCreateTestSet
|
|
CV_COUNT = _ml.CV_COUNT
|
|
CV_PORTION = _ml.CV_PORTION
|
|
class CvTrainTestSplit(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvTrainTestSplit, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvTrainTestSplit, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self, *args):
|
|
this = _ml.new_CvTrainTestSplit(*args)
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_setmethods__["train_sample_part_mode"] = _ml.CvTrainTestSplit_train_sample_part_mode_set
|
|
__swig_getmethods__["train_sample_part_mode"] = _ml.CvTrainTestSplit_train_sample_part_mode_get
|
|
if _newclass:train_sample_part_mode = _swig_property(_ml.CvTrainTestSplit_train_sample_part_mode_get, _ml.CvTrainTestSplit_train_sample_part_mode_set)
|
|
__swig_setmethods__["class_part_mode"] = _ml.CvTrainTestSplit_class_part_mode_set
|
|
__swig_getmethods__["class_part_mode"] = _ml.CvTrainTestSplit_class_part_mode_get
|
|
if _newclass:class_part_mode = _swig_property(_ml.CvTrainTestSplit_class_part_mode_get, _ml.CvTrainTestSplit_class_part_mode_set)
|
|
__swig_setmethods__["mix"] = _ml.CvTrainTestSplit_mix_set
|
|
__swig_getmethods__["mix"] = _ml.CvTrainTestSplit_mix_get
|
|
if _newclass:mix = _swig_property(_ml.CvTrainTestSplit_mix_get, _ml.CvTrainTestSplit_mix_set)
|
|
__swig_getmethods__["class_part"] = _ml.CvTrainTestSplit_class_part_get
|
|
if _newclass:class_part = _swig_property(_ml.CvTrainTestSplit_class_part_get)
|
|
__swig_getmethods__["train_sample_part"] = _ml.CvTrainTestSplit_train_sample_part_get
|
|
if _newclass:train_sample_part = _swig_property(_ml.CvTrainTestSplit_train_sample_part_get)
|
|
__swig_destroy__ = _ml.delete_CvTrainTestSplit
|
|
__del__ = lambda self : None;
|
|
CvTrainTestSplit_swigregister = _ml.CvTrainTestSplit_swigregister
|
|
CvTrainTestSplit_swigregister(CvTrainTestSplit)
|
|
|
|
class CvTrainTestSplit_class_part(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvTrainTestSplit_class_part, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvTrainTestSplit_class_part, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["count"] = _ml.CvTrainTestSplit_class_part_count_set
|
|
__swig_getmethods__["count"] = _ml.CvTrainTestSplit_class_part_count_get
|
|
if _newclass:count = _swig_property(_ml.CvTrainTestSplit_class_part_count_get, _ml.CvTrainTestSplit_class_part_count_set)
|
|
__swig_setmethods__["portion"] = _ml.CvTrainTestSplit_class_part_portion_set
|
|
__swig_getmethods__["portion"] = _ml.CvTrainTestSplit_class_part_portion_get
|
|
if _newclass:portion = _swig_property(_ml.CvTrainTestSplit_class_part_portion_get, _ml.CvTrainTestSplit_class_part_portion_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvTrainTestSplit_class_part()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvTrainTestSplit_class_part
|
|
__del__ = lambda self : None;
|
|
CvTrainTestSplit_class_part_swigregister = _ml.CvTrainTestSplit_class_part_swigregister
|
|
CvTrainTestSplit_class_part_swigregister(CvTrainTestSplit_class_part)
|
|
|
|
class CvTrainTestSplit_train_sample_part(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvTrainTestSplit_train_sample_part, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvTrainTestSplit_train_sample_part, name)
|
|
__repr__ = _swig_repr
|
|
__swig_setmethods__["count"] = _ml.CvTrainTestSplit_train_sample_part_count_set
|
|
__swig_getmethods__["count"] = _ml.CvTrainTestSplit_train_sample_part_count_get
|
|
if _newclass:count = _swig_property(_ml.CvTrainTestSplit_train_sample_part_count_get, _ml.CvTrainTestSplit_train_sample_part_count_set)
|
|
__swig_setmethods__["portion"] = _ml.CvTrainTestSplit_train_sample_part_portion_set
|
|
__swig_getmethods__["portion"] = _ml.CvTrainTestSplit_train_sample_part_portion_get
|
|
if _newclass:portion = _swig_property(_ml.CvTrainTestSplit_train_sample_part_portion_get, _ml.CvTrainTestSplit_train_sample_part_portion_set)
|
|
def __init__(self):
|
|
this = _ml.new_CvTrainTestSplit_train_sample_part()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvTrainTestSplit_train_sample_part
|
|
__del__ = lambda self : None;
|
|
CvTrainTestSplit_train_sample_part_swigregister = _ml.CvTrainTestSplit_train_sample_part_swigregister
|
|
CvTrainTestSplit_train_sample_part_swigregister(CvTrainTestSplit_train_sample_part)
|
|
|
|
class CvMLData(_object):
|
|
__swig_setmethods__ = {}
|
|
__setattr__ = lambda self, name, value: _swig_setattr(self, CvMLData, name, value)
|
|
__swig_getmethods__ = {}
|
|
__getattr__ = lambda self, name: _swig_getattr(self, CvMLData, name)
|
|
__repr__ = _swig_repr
|
|
def __init__(self):
|
|
this = _ml.new_CvMLData()
|
|
try: self.this.append(this)
|
|
except: self.this = this
|
|
__swig_destroy__ = _ml.delete_CvMLData
|
|
__del__ = lambda self : None;
|
|
def read_csv(self, *args): return _ml.CvMLData_read_csv(self, *args)
|
|
def get_values(self): return _ml.CvMLData_get_values(self)
|
|
def get_responses(self): return _ml.CvMLData_get_responses(self)
|
|
def get_missing(self): return _ml.CvMLData_get_missing(self)
|
|
def set_response_idx(self, *args): return _ml.CvMLData_set_response_idx(self, *args)
|
|
def get_response_idx(self): return _ml.CvMLData_get_response_idx(self)
|
|
def get_train_sample_idx(self): return _ml.CvMLData_get_train_sample_idx(self)
|
|
def get_test_sample_idx(self): return _ml.CvMLData_get_test_sample_idx(self)
|
|
def mix_train_and_test_idx(self): return _ml.CvMLData_mix_train_and_test_idx(self)
|
|
def set_train_test_split(self, *args): return _ml.CvMLData_set_train_test_split(self, *args)
|
|
def get_var_idx(self): return _ml.CvMLData_get_var_idx(self)
|
|
def chahge_var_idx(self, *args): return _ml.CvMLData_chahge_var_idx(self, *args)
|
|
def get_var_types(self): return _ml.CvMLData_get_var_types(self)
|
|
def get_var_type(self, *args): return _ml.CvMLData_get_var_type(self, *args)
|
|
def set_var_types(self, *args): return _ml.CvMLData_set_var_types(self, *args)
|
|
def change_var_type(self, *args): return _ml.CvMLData_change_var_type(self, *args)
|
|
def set_delimiter(self, *args): return _ml.CvMLData_set_delimiter(self, *args)
|
|
def get_delimiter(self): return _ml.CvMLData_get_delimiter(self)
|
|
def set_miss_ch(self, *args): return _ml.CvMLData_set_miss_ch(self, *args)
|
|
def get_miss_ch(self): return _ml.CvMLData_get_miss_ch(self)
|
|
CvMLData_swigregister = _ml.CvMLData_swigregister
|
|
CvMLData_swigregister(CvMLData)
|
|
|
|
|
|
|