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| CvSVM () |
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virtual | ~CvSVM () |
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| CvSVM (const CvMat *trainData, const CvMat *responses, const CvMat *varIdx=0, const CvMat *sampleIdx=0, CvSVMParams params=CvSVMParams()) |
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virtual bool | train (const CvMat *trainData, const CvMat *responses, const CvMat *varIdx=0, const CvMat *sampleIdx=0, CvSVMParams params=CvSVMParams()) |
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virtual bool | train_auto (const CvMat *trainData, const CvMat *responses, const CvMat *varIdx, const CvMat *sampleIdx, CvSVMParams params, int kfold=10, CvParamGrid Cgrid=get_default_grid(CvSVM::C), CvParamGrid gammaGrid=get_default_grid(CvSVM::GAMMA), CvParamGrid pGrid=get_default_grid(CvSVM::P), CvParamGrid nuGrid=get_default_grid(CvSVM::NU), CvParamGrid coeffGrid=get_default_grid(CvSVM::COEF), CvParamGrid degreeGrid=get_default_grid(CvSVM::DEGREE), bool balanced=false) |
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virtual float | predict (const CvMat *sample, bool returnDFVal=false) const |
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virtual float | predict (const CvMat *samples, CV_OUT CvMat *results) const |
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| CvSVM (const cv::Mat &trainData, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat(), CvSVMParams params=CvSVMParams()) |
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virtual bool | train (const cv::Mat &trainData, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat(), CvSVMParams params=CvSVMParams()) |
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virtual bool | train_auto (const cv::Mat &trainData, const cv::Mat &responses, const cv::Mat &varIdx, const cv::Mat &sampleIdx, CvSVMParams params, int k_fold=10, CvParamGrid Cgrid=CvSVM::get_default_grid(CvSVM::C), CvParamGrid gammaGrid=CvSVM::get_default_grid(CvSVM::GAMMA), CvParamGrid pGrid=CvSVM::get_default_grid(CvSVM::P), CvParamGrid nuGrid=CvSVM::get_default_grid(CvSVM::NU), CvParamGrid coeffGrid=CvSVM::get_default_grid(CvSVM::COEF), CvParamGrid degreeGrid=CvSVM::get_default_grid(CvSVM::DEGREE), bool balanced=false) |
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virtual float | predict (const cv::Mat &sample, bool returnDFVal=false) const |
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void | predict (cv::InputArray samples, cv::OutputArray results) const |
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virtual int | get_support_vector_count () const |
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virtual const float * | get_support_vector (int i) const |
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virtual CvSVMParams | get_params () const |
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virtual void | clear () |
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virtual void | write (CvFileStorage *storage, const char *name) const |
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virtual void | read (CvFileStorage *storage, CvFileNode *node) |
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int | get_var_count () const |
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| CvStatModel () |
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virtual | ~CvStatModel () |
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virtual void | save (const char *filename, const char *name=0) const |
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virtual void | load (const char *filename, const char *name=0) |
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virtual bool | set_params (const CvSVMParams ¶ms) |
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virtual bool | train1 (int sample_count, int var_count, const float **samples, const void *responses, double Cp, double Cn, CvMemStorage *_storage, double *alpha, double &rho) |
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virtual bool | do_train (int svm_type, int sample_count, int var_count, const float **samples, const CvMat *responses, CvMemStorage *_storage, double *alpha) |
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virtual void | create_kernel () |
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virtual void | create_solver () |
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virtual float | predict (const float *row_sample, int row_len, bool returnDFVal=false) const |
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virtual void | write_params (CvFileStorage *fs) const |
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virtual void | read_params (CvFileStorage *fs, CvFileNode *node) |
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void | optimize_linear_svm () |
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