# This file was automatically generated by SWIG (http://www.swig.org). # Version 1.3.40 # # Do not make changes to this file unless you know what you are doing--modify # the SWIG interface file instead. # This file is compatible with both classic and new-style classes. from sys import version_info if version_info >= (2,6,0): def swig_import_helper(): from os.path import dirname import imp fp = None try: fp, pathname, description = imp.find_module('_ml', [dirname(__file__)]) except ImportError: import _ml return _ml if fp is not None: try: _mod = imp.load_module('_ml', fp, pathname, description) finally: fp.close() return _mod _ml = swig_import_helper() del swig_import_helper else: import _ml del version_info try: _swig_property = property except NameError: pass # Python < 2.2 doesn't have 'property'. def _swig_setattr_nondynamic(self,class_type,name,value,static=1): if (name == "thisown"): return self.this.own(value) if (name == "this"): if type(value).__name__ == 'SwigPyObject': self.__dict__[name] = value return method = class_type.__swig_setmethods__.get(name,None) if method: return method(self,value) if (not static) or hasattr(self,name): self.__dict__[name] = value else: raise AttributeError("You cannot add attributes to %s" % self) def _swig_setattr(self,class_type,name,value): return _swig_setattr_nondynamic(self,class_type,name,value,0) def _swig_getattr(self,class_type,name): if (name == "thisown"): return self.this.own() method = class_type.__swig_getmethods__.get(name,None) if method: return method(self) raise AttributeError(name) def _swig_repr(self): try: strthis = "proxy of " + self.this.__repr__() except: strthis = "" return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,) try: _object = object _newclass = 1 except AttributeError: class _object : pass _newclass = 0 class CvRNG_Wrapper(_object): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvRNG_Wrapper, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvRNG_Wrapper, name) __repr__ = _swig_repr def __init__(self, *args): this = _ml.new_CvRNG_Wrapper(*args) try: self.this.append(this) except: self.this = this def ptr(self): return _ml.CvRNG_Wrapper_ptr(self) def ref(self): return _ml.CvRNG_Wrapper_ref(self) def __eq__(self, *args): return _ml.CvRNG_Wrapper___eq__(self, *args) def __ne__(self, *args): return _ml.CvRNG_Wrapper___ne__(self, *args) __swig_destroy__ = _ml.delete_CvRNG_Wrapper __del__ = lambda self : None; CvRNG_Wrapper_swigregister = _ml.CvRNG_Wrapper_swigregister CvRNG_Wrapper_swigregister(CvRNG_Wrapper) class CvSubdiv2DEdge_Wrapper(_object): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvSubdiv2DEdge_Wrapper, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvSubdiv2DEdge_Wrapper, name) __repr__ = _swig_repr def __init__(self, *args): this = _ml.new_CvSubdiv2DEdge_Wrapper(*args) try: self.this.append(this) except: self.this = this def ptr(self): return _ml.CvSubdiv2DEdge_Wrapper_ptr(self) def ref(self): return _ml.CvSubdiv2DEdge_Wrapper_ref(self) def __eq__(self, *args): return _ml.CvSubdiv2DEdge_Wrapper___eq__(self, *args) def __ne__(self, *args): return _ml.CvSubdiv2DEdge_Wrapper___ne__(self, *args) __swig_destroy__ = _ml.delete_CvSubdiv2DEdge_Wrapper __del__ = lambda self : None; CvSubdiv2DEdge_Wrapper_swigregister = _ml.CvSubdiv2DEdge_Wrapper_swigregister CvSubdiv2DEdge_Wrapper_swigregister(CvSubdiv2DEdge_Wrapper) import cv __doc__ = """Machine Learning The Machine Learning library (ML) is a set of classes and functions for statistical classification, regression and clustering of data. Most of the classification and regression algorithms are implemented as classes. As the algorithms have different sets of features (like ability to handle missing measurements, or categorical input variables etc.), there is only little common ground between the classes. This common ground is defined by the class CvStatModel that all the other ML classes are derived from. This wrapper was semi-automatically created from the C/C++ headers and therefore contains no Python documentation. Because all identifiers are identical to their C/C++ counterparts, you can consult the standard manuals that come with OpenCV. """ CV_LOG2PI = _ml.CV_LOG2PI CV_COL_SAMPLE = _ml.CV_COL_SAMPLE CV_ROW_SAMPLE = _ml.CV_ROW_SAMPLE class CvVectors(_object): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvVectors, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvVectors, name) __repr__ = _swig_repr __swig_setmethods__["type"] = _ml.CvVectors_type_set __swig_getmethods__["type"] = _ml.CvVectors_type_get if _newclass:type = _swig_property(_ml.CvVectors_type_get, _ml.CvVectors_type_set) __swig_setmethods__["dims"] = _ml.CvVectors_dims_set __swig_getmethods__["dims"] = _ml.CvVectors_dims_get if _newclass:dims = _swig_property(_ml.CvVectors_dims_get, _ml.CvVectors_dims_set) __swig_setmethods__["count"] = _ml.CvVectors_count_set __swig_getmethods__["count"] = _ml.CvVectors_count_get if _newclass:count = _swig_property(_ml.CvVectors_count_get, _ml.CvVectors_count_set) __swig_setmethods__["next"] = _ml.CvVectors_next_set __swig_getmethods__["next"] = _ml.CvVectors_next_get if _newclass:next = _swig_property(_ml.CvVectors_next_get, _ml.CvVectors_next_set) __swig_getmethods__["data"] = _ml.CvVectors_data_get if _newclass:data = _swig_property(_ml.CvVectors_data_get) def __init__(self): this = _ml.new_CvVectors() try: self.this.append(this) except: self.this = this __swig_destroy__ = _ml.delete_CvVectors __del__ = lambda self : None; CvVectors_swigregister = _ml.CvVectors_swigregister CvVectors_swigregister(CvVectors) class CvVectors_data(_object): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvVectors_data, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvVectors_data, name) __repr__ = _swig_repr __swig_setmethods__["ptr"] = _ml.CvVectors_data_ptr_set __swig_getmethods__["ptr"] = _ml.CvVectors_data_ptr_get if _newclass:ptr = _swig_property(_ml.CvVectors_data_ptr_get, _ml.CvVectors_data_ptr_set) __swig_setmethods__["fl"] = _ml.CvVectors_data_fl_set __swig_getmethods__["fl"] = _ml.CvVectors_data_fl_get if _newclass:fl = _swig_property(_ml.CvVectors_data_fl_get, _ml.CvVectors_data_fl_set) __swig_setmethods__["db"] = _ml.CvVectors_data_db_set __swig_getmethods__["db"] = _ml.CvVectors_data_db_get if _newclass:db = _swig_property(_ml.CvVectors_data_db_get, _ml.CvVectors_data_db_set) def __init__(self): this = _ml.new_CvVectors_data() try: self.this.append(this) except: self.this = this __swig_destroy__ = _ml.delete_CvVectors_data __del__ = lambda self : None; CvVectors_data_swigregister = _ml.CvVectors_data_swigregister CvVectors_data_swigregister(CvVectors_data) CV_VAR_NUMERICAL = _ml.CV_VAR_NUMERICAL CV_VAR_ORDERED = _ml.CV_VAR_ORDERED CV_VAR_CATEGORICAL = _ml.CV_VAR_CATEGORICAL CV_TYPE_NAME_ML_SVM = _ml.CV_TYPE_NAME_ML_SVM CV_TYPE_NAME_ML_KNN = _ml.CV_TYPE_NAME_ML_KNN CV_TYPE_NAME_ML_NBAYES = _ml.CV_TYPE_NAME_ML_NBAYES CV_TYPE_NAME_ML_EM = _ml.CV_TYPE_NAME_ML_EM CV_TYPE_NAME_ML_BOOSTING = _ml.CV_TYPE_NAME_ML_BOOSTING CV_TYPE_NAME_ML_TREE = _ml.CV_TYPE_NAME_ML_TREE CV_TYPE_NAME_ML_ANN_MLP = _ml.CV_TYPE_NAME_ML_ANN_MLP CV_TYPE_NAME_ML_CNN = _ml.CV_TYPE_NAME_ML_CNN CV_TYPE_NAME_ML_RTREES = _ml.CV_TYPE_NAME_ML_RTREES CV_TRAIN_ERROR = _ml.CV_TRAIN_ERROR CV_TEST_ERROR = _ml.CV_TEST_ERROR class CvStatModel(_object): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvStatModel, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvStatModel, name) __repr__ = _swig_repr def __init__(self): this = _ml.new_CvStatModel() try: self.this.append(this) except: self.this = this __swig_destroy__ = _ml.delete_CvStatModel __del__ = lambda self : None; def clear(self): return _ml.CvStatModel_clear(self) def save(self, *args): return _ml.CvStatModel_save(self, *args) def load(self, *args): return _ml.CvStatModel_load(self, *args) def write(self, *args): return _ml.CvStatModel_write(self, *args) def read(self, *args): return _ml.CvStatModel_read(self, *args) CvStatModel_swigregister = _ml.CvStatModel_swigregister CvStatModel_swigregister(CvStatModel) class CvParamGrid(_object): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvParamGrid, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvParamGrid, name) __repr__ = _swig_repr SVM_C = _ml.CvParamGrid_SVM_C SVM_GAMMA = _ml.CvParamGrid_SVM_GAMMA SVM_P = _ml.CvParamGrid_SVM_P SVM_NU = _ml.CvParamGrid_SVM_NU SVM_COEF = _ml.CvParamGrid_SVM_COEF SVM_DEGREE = _ml.CvParamGrid_SVM_DEGREE def __init__(self, *args): this = _ml.new_CvParamGrid(*args) try: self.this.append(this) except: self.this = this def check(self): return _ml.CvParamGrid_check(self) __swig_setmethods__["min_val"] = _ml.CvParamGrid_min_val_set __swig_getmethods__["min_val"] = _ml.CvParamGrid_min_val_get if _newclass:min_val = _swig_property(_ml.CvParamGrid_min_val_get, _ml.CvParamGrid_min_val_set) __swig_setmethods__["max_val"] = _ml.CvParamGrid_max_val_set __swig_getmethods__["max_val"] = _ml.CvParamGrid_max_val_get if _newclass:max_val = _swig_property(_ml.CvParamGrid_max_val_get, _ml.CvParamGrid_max_val_set) __swig_setmethods__["step"] = _ml.CvParamGrid_step_set __swig_getmethods__["step"] = _ml.CvParamGrid_step_get if _newclass:step = _swig_property(_ml.CvParamGrid_step_get, _ml.CvParamGrid_step_set) __swig_destroy__ = _ml.delete_CvParamGrid __del__ = lambda self : None; CvParamGrid_swigregister = _ml.CvParamGrid_swigregister CvParamGrid_swigregister(CvParamGrid) class CvNormalBayesClassifier(CvStatModel): __swig_setmethods__ = {} for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{})) __setattr__ = lambda self, name, value: _swig_setattr(self, CvNormalBayesClassifier, name, value) __swig_getmethods__ = {} for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{})) __getattr__ = lambda self, name: _swig_getattr(self, CvNormalBayesClassifier, name) __repr__ = _swig_repr __swig_destroy__ = _ml.delete_CvNormalBayesClassifier __del__ = lambda self : None; def __init__(self, *args): this = _ml.new_CvNormalBayesClassifier(*args) try: self.this.append(this) except: self.this = this def train(self, *args): return _ml.CvNormalBayesClassifier_train(self, *args) def predict(self, *args): return _ml.CvNormalBayesClassifier_predict(self, *args) def clear(self): return _ml.CvNormalBayesClassifier_clear(self) def write(self, *args): return _ml.CvNormalBayesClassifier_write(self, *args) def read(self, *args): return _ml.CvNormalBayesClassifier_read(self, *args) CvNormalBayesClassifier_swigregister = _ml.CvNormalBayesClassifier_swigregister CvNormalBayesClassifier_swigregister(CvNormalBayesClassifier) class CvKNearest(CvStatModel): __swig_setmethods__ = {} for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{})) __setattr__ = lambda self, name, value: _swig_setattr(self, CvKNearest, name, value) __swig_getmethods__ = {} for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{})) __getattr__ = lambda self, name: _swig_getattr(self, CvKNearest, name) __repr__ = _swig_repr __swig_destroy__ = _ml.delete_CvKNearest __del__ = lambda self : None; def __init__(self, *args): this = _ml.new_CvKNearest(*args) try: self.this.append(this) except: self.this = this def train(self, *args): return _ml.CvKNearest_train(self, *args) def find_nearest(self, *args): return _ml.CvKNearest_find_nearest(self, *args) def clear(self): return _ml.CvKNearest_clear(self) def get_max_k(self): return _ml.CvKNearest_get_max_k(self) def get_var_count(self): return _ml.CvKNearest_get_var_count(self) def get_sample_count(self): return _ml.CvKNearest_get_sample_count(self) def is_regression(self): return _ml.CvKNearest_is_regression(self) CvKNearest_swigregister = _ml.CvKNearest_swigregister CvKNearest_swigregister(CvKNearest) class CvSVMParams(_object): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvSVMParams, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvSVMParams, name) __repr__ = _swig_repr def __init__(self, *args): this = _ml.new_CvSVMParams(*args) try: self.this.append(this) except: self.this = this __swig_setmethods__["svm_type"] = _ml.CvSVMParams_svm_type_set __swig_getmethods__["svm_type"] = _ml.CvSVMParams_svm_type_get if _newclass:svm_type = _swig_property(_ml.CvSVMParams_svm_type_get, _ml.CvSVMParams_svm_type_set) __swig_setmethods__["kernel_type"] = _ml.CvSVMParams_kernel_type_set __swig_getmethods__["kernel_type"] = _ml.CvSVMParams_kernel_type_get if _newclass:kernel_type = _swig_property(_ml.CvSVMParams_kernel_type_get, _ml.CvSVMParams_kernel_type_set) __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) __swig_setmethods__["gamma"] = _ml.CvSVMParams_gamma_set __swig_getmethods__["gamma"] = _ml.CvSVMParams_gamma_get if _newclass:gamma = _swig_property(_ml.CvSVMParams_gamma_get, _ml.CvSVMParams_gamma_set) __swig_setmethods__["coef0"] = _ml.CvSVMParams_coef0_set __swig_getmethods__["coef0"] = _ml.CvSVMParams_coef0_get if _newclass:coef0 = _swig_property(_ml.CvSVMParams_coef0_get, _ml.CvSVMParams_coef0_set) __swig_setmethods__["C"] = _ml.CvSVMParams_C_set __swig_getmethods__["C"] = _ml.CvSVMParams_C_get if _newclass:C = _swig_property(_ml.CvSVMParams_C_get, _ml.CvSVMParams_C_set) __swig_setmethods__["nu"] = _ml.CvSVMParams_nu_set __swig_getmethods__["nu"] = _ml.CvSVMParams_nu_get if _newclass:nu = _swig_property(_ml.CvSVMParams_nu_get, _ml.CvSVMParams_nu_set) __swig_setmethods__["p"] = _ml.CvSVMParams_p_set __swig_getmethods__["p"] = _ml.CvSVMParams_p_get if _newclass:p = _swig_property(_ml.CvSVMParams_p_get, _ml.CvSVMParams_p_set) __swig_setmethods__["class_weights"] = _ml.CvSVMParams_class_weights_set __swig_getmethods__["class_weights"] = _ml.CvSVMParams_class_weights_get 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): __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, CvDTreeTrainData, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, CvDTreeTrainData, name) __repr__ = _swig_repr def __init__(self, *args): this = _ml.new_CvDTreeTrainData(*args) try: self.this.append(this) except: self.this = this __swig_destroy__ = _ml.delete_CvDTreeTrainData __del__ = lambda self : None; def set_data(self, *args): return _ml.CvDTreeTrainData_set_data(self, *args) def do_responses_copy(self): return _ml.CvDTreeTrainData_do_responses_copy(self) def get_vectors(self, *args): return _ml.CvDTreeTrainData_get_vectors(self, *args) def subsample_data(self, *args): return _ml.CvDTreeTrainData_subsample_data(self, *args) def write_params(self, *args): return _ml.CvDTreeTrainData_write_params(self, *args) def read_params(self, *args): return _ml.CvDTreeTrainData_read_params(self, *args) def clear(self): return _ml.CvDTreeTrainData_clear(self) def get_num_classes(self): return _ml.CvDTreeTrainData_get_num_classes(self) def get_var_type(self, *args): return _ml.CvDTreeTrainData_get_var_type(self, *args) def get_work_var_count(self): return _ml.CvDTreeTrainData_get_work_var_count(self) def get_ord_responses(self, *args): return _ml.CvDTreeTrainData_get_ord_responses(self, *args) def get_class_labels(self, *args): return _ml.CvDTreeTrainData_get_class_labels(self, *args) def get_cv_labels(self, *args): return _ml.CvDTreeTrainData_get_cv_labels(self, *args) def get_sample_indices(self, *args): return _ml.CvDTreeTrainData_get_sample_indices(self, *args) def get_cat_var_data(self, *args): return _ml.CvDTreeTrainData_get_cat_var_data(self, *args) def get_ord_var_data(self, *args): return _ml.CvDTreeTrainData_get_ord_var_data(self, *args) def get_child_buf_idx(self, *args): return _ml.CvDTreeTrainData_get_child_buf_idx(self, *args) def set_params(self, *args): return _ml.CvDTreeTrainData_set_params(self, *args) def new_node(self, *args): return _ml.CvDTreeTrainData_new_node(self, *args) def new_split_ord(self, *args): return _ml.CvDTreeTrainData_new_split_ord(self, *args) def new_split_cat(self, *args): return _ml.CvDTreeTrainData_new_split_cat(self, *args) def free_node_data(self, *args): return _ml.CvDTreeTrainData_free_node_data(self, *args) def free_train_data(self): return _ml.CvDTreeTrainData_free_train_data(self) def free_node(self, *args): return _ml.CvDTreeTrainData_free_node(self, *args) def get_pred_float_buf(self): return _ml.CvDTreeTrainData_get_pred_float_buf(self) def get_pred_int_buf(self): return _ml.CvDTreeTrainData_get_pred_int_buf(self) def get_resp_float_buf(self): return _ml.CvDTreeTrainData_get_resp_float_buf(self) def get_resp_int_buf(self): return _ml.CvDTreeTrainData_get_resp_int_buf(self) def get_cv_lables_buf(self): return _ml.CvDTreeTrainData_get_cv_lables_buf(self) def get_sample_idx_buf(self): return _ml.CvDTreeTrainData_get_sample_idx_buf(self) __swig_setmethods__["pred_float_buf"] = _ml.CvDTreeTrainData_pred_float_buf_set __swig_getmethods__["pred_float_buf"] = _ml.CvDTreeTrainData_pred_float_buf_get if _newclass:pred_float_buf = _swig_property(_ml.CvDTreeTrainData_pred_float_buf_get, _ml.CvDTreeTrainData_pred_float_buf_set) __swig_setmethods__["pred_int_buf"] = _ml.CvDTreeTrainData_pred_int_buf_set __swig_getmethods__["pred_int_buf"] = _ml.CvDTreeTrainData_pred_int_buf_get if _newclass:pred_int_buf = _swig_property(_ml.CvDTreeTrainData_pred_int_buf_get, _ml.CvDTreeTrainData_pred_int_buf_set) __swig_setmethods__["resp_float_buf"] = _ml.CvDTreeTrainData_resp_float_buf_set __swig_getmethods__["resp_float_buf"] = _ml.CvDTreeTrainData_resp_float_buf_get if _newclass:resp_float_buf = _swig_property(_ml.CvDTreeTrainData_resp_float_buf_get, _ml.CvDTreeTrainData_resp_float_buf_set) __swig_setmethods__["resp_int_buf"] = _ml.CvDTreeTrainData_resp_int_buf_set __swig_getmethods__["resp_int_buf"] = _ml.CvDTreeTrainData_resp_int_buf_get if _newclass:resp_int_buf = _swig_property(_ml.CvDTreeTrainData_resp_int_buf_get, _ml.CvDTreeTrainData_resp_int_buf_set) __swig_setmethods__["cv_lables_buf"] = _ml.CvDTreeTrainData_cv_lables_buf_set __swig_getmethods__["cv_lables_buf"] = _ml.CvDTreeTrainData_cv_lables_buf_get if _newclass:cv_lables_buf = _swig_property(_ml.CvDTreeTrainData_cv_lables_buf_get, _ml.CvDTreeTrainData_cv_lables_buf_set) __swig_setmethods__["sample_idx_buf"] = _ml.CvDTreeTrainData_sample_idx_buf_set __swig_getmethods__["sample_idx_buf"] = _ml.CvDTreeTrainData_sample_idx_buf_get if _newclass:sample_idx_buf = _swig_property(_ml.CvDTreeTrainData_sample_idx_buf_get, _ml.CvDTreeTrainData_sample_idx_buf_set) __swig_setmethods__["sample_count"] = _ml.CvDTreeTrainData_sample_count_set __swig_getmethods__["sample_count"] = _ml.CvDTreeTrainData_sample_count_get if _newclass:sample_count = _swig_property(_ml.CvDTreeTrainData_sample_count_get, _ml.CvDTreeTrainData_sample_count_set) __swig_setmethods__["var_all"] = _ml.CvDTreeTrainData_var_all_set __swig_getmethods__["var_all"] = _ml.CvDTreeTrainData_var_all_get if _newclass:var_all = _swig_property(_ml.CvDTreeTrainData_var_all_get, _ml.CvDTreeTrainData_var_all_set) __swig_setmethods__["var_count"] = _ml.CvDTreeTrainData_var_count_set __swig_getmethods__["var_count"] = _ml.CvDTreeTrainData_var_count_get if _newclass:var_count = _swig_property(_ml.CvDTreeTrainData_var_count_get, _ml.CvDTreeTrainData_var_count_set) __swig_setmethods__["max_c_count"] = _ml.CvDTreeTrainData_max_c_count_set __swig_getmethods__["max_c_count"] = _ml.CvDTreeTrainData_max_c_count_get if _newclass:max_c_count = _swig_property(_ml.CvDTreeTrainData_max_c_count_get, _ml.CvDTreeTrainData_max_c_count_set) __swig_setmethods__["ord_var_count"] = _ml.CvDTreeTrainData_ord_var_count_set __swig_getmethods__["ord_var_count"] = _ml.CvDTreeTrainData_ord_var_count_get if _newclass:ord_var_count = _swig_property(_ml.CvDTreeTrainData_ord_var_count_get, _ml.CvDTreeTrainData_ord_var_count_set) __swig_setmethods__["cat_var_count"] = _ml.CvDTreeTrainData_cat_var_count_set __swig_getmethods__["cat_var_count"] = _ml.CvDTreeTrainData_cat_var_count_get if _newclass:cat_var_count = _swig_property(_ml.CvDTreeTrainData_cat_var_count_get, _ml.CvDTreeTrainData_cat_var_count_set) __swig_setmethods__["work_var_count"] = _ml.CvDTreeTrainData_work_var_count_set __swig_getmethods__["work_var_count"] = _ml.CvDTreeTrainData_work_var_count_get if _newclass:work_var_count = _swig_property(_ml.CvDTreeTrainData_work_var_count_get, _ml.CvDTreeTrainData_work_var_count_set) __swig_setmethods__["have_labels"] = _ml.CvDTreeTrainData_have_labels_set __swig_getmethods__["have_labels"] = _ml.CvDTreeTrainData_have_labels_get if _newclass:have_labels = _swig_property(_ml.CvDTreeTrainData_have_labels_get, _ml.CvDTreeTrainData_have_labels_set) __swig_setmethods__["have_priors"] = _ml.CvDTreeTrainData_have_priors_set __swig_getmethods__["have_priors"] = _ml.CvDTreeTrainData_have_priors_get if _newclass:have_priors = _swig_property(_ml.CvDTreeTrainData_have_priors_get, _ml.CvDTreeTrainData_have_priors_set) __swig_setmethods__["is_classifier"] = _ml.CvDTreeTrainData_is_classifier_set __swig_getmethods__["is_classifier"] = _ml.CvDTreeTrainData_is_classifier_get if _newclass:is_classifier = _swig_property(_ml.CvDTreeTrainData_is_classifier_get, _ml.CvDTreeTrainData_is_classifier_set) __swig_setmethods__["tflag"] = _ml.CvDTreeTrainData_tflag_set __swig_getmethods__["tflag"] = _ml.CvDTreeTrainData_tflag_get if _newclass:tflag = _swig_property(_ml.CvDTreeTrainData_tflag_get, _ml.CvDTreeTrainData_tflag_set) __swig_setmethods__["train_data"] = _ml.CvDTreeTrainData_train_data_set __swig_getmethods__["train_data"] = _ml.CvDTreeTrainData_train_data_get if _newclass:train_data = _swig_property(_ml.CvDTreeTrainData_train_data_get, _ml.CvDTreeTrainData_train_data_set) __swig_setmethods__["responses"] = _ml.CvDTreeTrainData_responses_set __swig_getmethods__["responses"] = _ml.CvDTreeTrainData_responses_get if _newclass:responses = _swig_property(_ml.CvDTreeTrainData_responses_get, _ml.CvDTreeTrainData_responses_set) __swig_setmethods__["responses_copy"] = _ml.CvDTreeTrainData_responses_copy_set __swig_getmethods__["responses_copy"] = _ml.CvDTreeTrainData_responses_copy_get if _newclass:responses_copy = _swig_property(_ml.CvDTreeTrainData_responses_copy_get, _ml.CvDTreeTrainData_responses_copy_set) __swig_setmethods__["buf_count"] = _ml.CvDTreeTrainData_buf_count_set __swig_getmethods__["buf_count"] = _ml.CvDTreeTrainData_buf_count_get if _newclass:buf_count = _swig_property(_ml.CvDTreeTrainData_buf_count_get, _ml.CvDTreeTrainData_buf_count_set) __swig_setmethods__["buf_size"] = _ml.CvDTreeTrainData_buf_size_set __swig_getmethods__["buf_size"] = _ml.CvDTreeTrainData_buf_size_get if _newclass:buf_size = _swig_property(_ml.CvDTreeTrainData_buf_size_get, _ml.CvDTreeTrainData_buf_size_set) __swig_setmethods__["shared"] = _ml.CvDTreeTrainData_shared_set __swig_getmethods__["shared"] = _ml.CvDTreeTrainData_shared_get if _newclass:shared = _swig_property(_ml.CvDTreeTrainData_shared_get, _ml.CvDTreeTrainData_shared_set) __swig_setmethods__["is_buf_16u"] = _ml.CvDTreeTrainData_is_buf_16u_set __swig_getmethods__["is_buf_16u"] = _ml.CvDTreeTrainData_is_buf_16u_get if _newclass:is_buf_16u = _swig_property(_ml.CvDTreeTrainData_is_buf_16u_get, _ml.CvDTreeTrainData_is_buf_16u_set) __swig_setmethods__["cat_count"] = _ml.CvDTreeTrainData_cat_count_set __swig_getmethods__["cat_count"] = _ml.CvDTreeTrainData_cat_count_get if _newclass:cat_count = _swig_property(_ml.CvDTreeTrainData_cat_count_get, _ml.CvDTreeTrainData_cat_count_set) __swig_setmethods__["cat_ofs"] = _ml.CvDTreeTrainData_cat_ofs_set __swig_getmethods__["cat_ofs"] = _ml.CvDTreeTrainData_cat_ofs_get if _newclass:cat_ofs = _swig_property(_ml.CvDTreeTrainData_cat_ofs_get, _ml.CvDTreeTrainData_cat_ofs_set) __swig_setmethods__["cat_map"] = _ml.CvDTreeTrainData_cat_map_set __swig_getmethods__["cat_map"] = _ml.CvDTreeTrainData_cat_map_get if _newclass:cat_map = _swig_property(_ml.CvDTreeTrainData_cat_map_get, _ml.CvDTreeTrainData_cat_map_set) __swig_setmethods__["counts"] = _ml.CvDTreeTrainData_counts_set __swig_getmethods__["counts"] = _ml.CvDTreeTrainData_counts_get if _newclass:counts = _swig_property(_ml.CvDTreeTrainData_counts_get, _ml.CvDTreeTrainData_counts_set) __swig_setmethods__["buf"] = _ml.CvDTreeTrainData_buf_set __swig_getmethods__["buf"] = _ml.CvDTreeTrainData_buf_get if _newclass:buf = _swig_property(_ml.CvDTreeTrainData_buf_get, _ml.CvDTreeTrainData_buf_set) __swig_setmethods__["direction"] = _ml.CvDTreeTrainData_direction_set __swig_getmethods__["direction"] = _ml.CvDTreeTrainData_direction_get if _newclass:direction = _swig_property(_ml.CvDTreeTrainData_direction_get, _ml.CvDTreeTrainData_direction_set) __swig_setmethods__["split_buf"] = _ml.CvDTreeTrainData_split_buf_set __swig_getmethods__["split_buf"] = _ml.CvDTreeTrainData_split_buf_get if _newclass:split_buf = _swig_property(_ml.CvDTreeTrainData_split_buf_get, _ml.CvDTreeTrainData_split_buf_set) __swig_setmethods__["var_idx"] = _ml.CvDTreeTrainData_var_idx_set __swig_getmethods__["var_idx"] = _ml.CvDTreeTrainData_var_idx_get if _newclass:var_idx = _swig_property(_ml.CvDTreeTrainData_var_idx_get, _ml.CvDTreeTrainData_var_idx_set) __swig_setmethods__["var_type"] = _ml.CvDTreeTrainData_var_type_set __swig_getmethods__["var_type"] = _ml.CvDTreeTrainData_var_type_get if _newclass:var_type = _swig_property(_ml.CvDTreeTrainData_var_type_get, _ml.CvDTreeTrainData_var_type_set) __swig_setmethods__["priors"] = _ml.CvDTreeTrainData_priors_set __swig_getmethods__["priors"] = _ml.CvDTreeTrainData_priors_get if _newclass:priors = _swig_property(_ml.CvDTreeTrainData_priors_get, _ml.CvDTreeTrainData_priors_set) __swig_setmethods__["priors_mult"] = _ml.CvDTreeTrainData_priors_mult_set __swig_getmethods__["priors_mult"] = _ml.CvDTreeTrainData_priors_mult_get if _newclass:priors_mult = _swig_property(_ml.CvDTreeTrainData_priors_mult_get, _ml.CvDTreeTrainData_priors_mult_set) __swig_setmethods__["params"] = _ml.CvDTreeTrainData_params_set __swig_getmethods__["params"] = _ml.CvDTreeTrainData_params_get if _newclass:params = _swig_property(_ml.CvDTreeTrainData_params_get, _ml.CvDTreeTrainData_params_set) __swig_setmethods__["tree_storage"] = _ml.CvDTreeTrainData_tree_storage_set __swig_getmethods__["tree_storage"] = _ml.CvDTreeTrainData_tree_storage_get if _newclass:tree_storage = _swig_property(_ml.CvDTreeTrainData_tree_storage_get, _ml.CvDTreeTrainData_tree_storage_set) __swig_setmethods__["temp_storage"] = _ml.CvDTreeTrainData_temp_storage_set __swig_getmethods__["temp_storage"] = _ml.CvDTreeTrainData_temp_storage_get if _newclass:temp_storage = _swig_property(_ml.CvDTreeTrainData_temp_storage_get, _ml.CvDTreeTrainData_temp_storage_set) __swig_setmethods__["data_root"] = _ml.CvDTreeTrainData_data_root_set __swig_getmethods__["data_root"] = _ml.CvDTreeTrainData_data_root_get if _newclass:data_root = _swig_property(_ml.CvDTreeTrainData_data_root_get, _ml.CvDTreeTrainData_data_root_set) __swig_setmethods__["node_heap"] = _ml.CvDTreeTrainData_node_heap_set __swig_getmethods__["node_heap"] = _ml.CvDTreeTrainData_node_heap_get if _newclass:node_heap = _swig_property(_ml.CvDTreeTrainData_node_heap_get, _ml.CvDTreeTrainData_node_heap_set) __swig_setmethods__["split_heap"] = _ml.CvDTreeTrainData_split_heap_set __swig_getmethods__["split_heap"] = _ml.CvDTreeTrainData_split_heap_get if _newclass:split_heap = _swig_property(_ml.CvDTreeTrainData_split_heap_get, _ml.CvDTreeTrainData_split_heap_set) __swig_setmethods__["cv_heap"] = _ml.CvDTreeTrainData_cv_heap_set __swig_getmethods__["cv_heap"] = _ml.CvDTreeTrainData_cv_heap_get if _newclass:cv_heap = _swig_property(_ml.CvDTreeTrainData_cv_heap_get, _ml.CvDTreeTrainData_cv_heap_set) __swig_setmethods__["nv_heap"] = _ml.CvDTreeTrainData_nv_heap_set __swig_getmethods__["nv_heap"] = _ml.CvDTreeTrainData_nv_heap_get if _newclass:nv_heap = _swig_property(_ml.CvDTreeTrainData_nv_heap_get, _ml.CvDTreeTrainData_nv_heap_set) __swig_setmethods__["rng"] = _ml.CvDTreeTrainData_rng_set __swig_getmethods__["rng"] = _ml.CvDTreeTrainData_rng_get if _newclass:rng = _swig_property(_ml.CvDTreeTrainData_rng_get, _ml.CvDTreeTrainData_rng_set) CvDTreeTrainData_swigregister = _ml.CvDTreeTrainData_swigregister CvDTreeTrainData_swigregister(CvDTreeTrainData) class CvDTree(CvStatModel): __swig_setmethods__ = {} for _s in [CvStatModel]: __swig_setmethods__.update(getattr(_s,'__swig_setmethods__',{})) __setattr__ = lambda self, name, value: _swig_setattr(self, CvDTree, name, value) __swig_getmethods__ = {} for _s in [CvStatModel]: __swig_getmethods__.update(getattr(_s,'__swig_getmethods__',{})) __getattr__ = lambda self, name: _swig_getattr(self, CvDTree, name) __repr__ = _swig_repr def __init__(self): this = _ml.new_CvDTree() try: self.this.append(this) except: self.this = this __swig_destroy__ = _ml.delete_CvDTree __del__ = lambda self : None; def calc_error(self, *args): return _ml.CvDTree_calc_error(self, *args) def train(self, *args): return _ml.CvDTree_train(self, *args) def predict(self, *args): return _ml.CvDTree_predict(self, *args) def get_var_importance(self): return _ml.CvDTree_get_var_importance(self) def clear(self): return _ml.CvDTree_clear(self) def read(self, *args): return _ml.CvDTree_read(self, *args) def write(self, *args): return _ml.CvDTree_write(self, *args) def get_root(self): return _ml.CvDTree_get_root(self) def get_pruned_tree_idx(self): return _ml.CvDTree_get_pruned_tree_idx(self) def get_data(self): return _ml.CvDTree_get_data(self) __swig_setmethods__["pruned_tree_idx"] = _ml.CvDTree_pruned_tree_idx_set __swig_getmethods__["pruned_tree_idx"] = _ml.CvDTree_pruned_tree_idx_get if _newclass:pruned_tree_idx = _swig_property(_ml.CvDTree_pruned_tree_idx_get, _ml.CvDTree_pruned_tree_idx_set) CvDTree_swigregister = _ml.CvDTree_swigregister CvDTree_swigregister(CvDTree) class CvForestTree(CvDTree): __swig_setmethods__ = {} 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)