| begin_ | ProgressLogger | mutableprotected | 
  | BORDER_LENGTH enum value | SVMWrapper |  | 
  | border_length_ | SVMWrapper | private | 
  | C enum value | SVMWrapper |  | 
  | calculateGaussTable(Size border_length, DoubleReal sigma, std::vector< DoubleReal > &gauss_table) | SVMWrapper | static | 
  | CMD enum value | ProgressLogger |  | 
  | computeKernelMatrix(svm_problem *problem1, svm_problem *problem2) | SVMWrapper |  | 
  | computeKernelMatrix(const SVMData &problem1, const SVMData &problem2) | SVMWrapper |  | 
  | createRandomPartitions(svm_problem *problem, Size number, std::vector< svm_problem * > &partitions) | SVMWrapper | static | 
  | createRandomPartitions(const SVMData &problem, Size number, std::vector< SVMData > &problems) | SVMWrapper | static | 
  | DEGREE enum value | SVMWrapper |  | 
  | dlg_ | ProgressLogger | mutableprotected | 
  | end_ | ProgressLogger | mutableprotected | 
  | endProgress() const | ProgressLogger |  | 
  | GAMMA enum value | SVMWrapper |  | 
  | gauss_table_ | SVMWrapper | private | 
  | gauss_tables_ | SVMWrapper | private | 
  | getDecisionValues(svm_problem *data, std::vector< DoubleReal > &decision_values) | SVMWrapper |  | 
  | getDoubleParameter(SVM_parameter_type type) | SVMWrapper |  | 
  | getIntParameter(SVM_parameter_type type) | SVMWrapper |  | 
  | getLabels(svm_problem *problem, std::vector< DoubleReal > &labels) | SVMWrapper | static | 
  | getLogType() const | ProgressLogger |  | 
  | getNumberOfEnclosedPoints_(DoubleReal m1, DoubleReal m2, const std::vector< std::pair< DoubleReal, DoubleReal > > &points) | SVMWrapper | private | 
  | getPValue(DoubleReal sigma1, DoubleReal sigma2, std::pair< DoubleReal, DoubleReal > point) | SVMWrapper |  | 
  | getSignificanceBorders(svm_problem *data, std::pair< DoubleReal, DoubleReal > &borders, DoubleReal confidence=0.95, Size number_of_runs=5, Size number_of_partitions=5, DoubleReal step_size=0.01, Size max_iterations=1000000) | SVMWrapper |  | 
  | getSignificanceBorders(const SVMData &data, std::pair< DoubleReal, DoubleReal > &sigmas, DoubleReal confidence=0.95, Size number_of_runs=5, Size number_of_partitions=5, DoubleReal step_size=0.01, Size max_iterations=1000000) | SVMWrapper |  | 
  | getSVCProbabilities(struct svm_problem *problem, std::vector< DoubleReal > &probabilities, std::vector< DoubleReal > &prediction_labels) | SVMWrapper |  | 
  | getSVRProbability() | SVMWrapper |  | 
  | GUI enum value | ProgressLogger |  | 
  | initParameters_() | SVMWrapper | private | 
  | KERNEL_TYPE enum value | SVMWrapper |  | 
  | kernel_type_ | SVMWrapper | private | 
  | kernelOligo(const std::vector< std::pair< int, double > > &x, const std::vector< std::pair< int, double > > &y, const std::vector< double > &gauss_table, int max_distance=-1) | SVMWrapper | static | 
  | kernelOligo(const svm_node *x, const svm_node *y, const std::vector< DoubleReal > &gauss_table, DoubleReal sigma_square=0, Size max_distance=50) | SVMWrapper | static | 
  | last_invoke_ | ProgressLogger | mutableprotected | 
  | loadModel(std::string modelFilename) | SVMWrapper |  | 
  | LogType enum name | ProgressLogger |  | 
  | mergePartitions(const std::vector< svm_problem * > &problems, Size except) | SVMWrapper | static | 
  | mergePartitions(const std::vector< SVMData > &problems, Size except, SVMData &merged_problem) | SVMWrapper | static | 
  | model_ | SVMWrapper | private | 
  | nextGrid_(const std::vector< DoubleReal > &start_values, const std::vector< DoubleReal > &step_sizes, const std::vector< DoubleReal > &end_values, const bool additive_step_sizes, std::vector< DoubleReal > &actual_values) | SVMWrapper | private | 
  | NONE enum value | ProgressLogger |  | 
  | NU enum value | SVMWrapper |  | 
  | OLIGO enum value | SVMWrapper |  | 
  | OLIGO_COMBINED enum value | SVMWrapper |  | 
  | P enum value | SVMWrapper |  | 
  | param_ | SVMWrapper | private | 
  | performCrossValidation(svm_problem *problem_ul, const SVMData &problem_l, const bool is_labeled, const std::map< SVM_parameter_type, DoubleReal > &start_values_map, const std::map< SVM_parameter_type, DoubleReal > &step_sizes_map, const std::map< SVM_parameter_type, DoubleReal > &end_values_map, Size number_of_partitions, Size number_of_runs, std::map< SVM_parameter_type, DoubleReal > &best_parameters, bool additive_step_sizes=true, bool output=false, String performances_file_name="performances.txt", bool mcc_as_performance_measure=false) | SVMWrapper |  | 
  | predict(struct svm_problem *problem, std::vector< DoubleReal > &predicted_labels) | SVMWrapper |  | 
  | predict(const SVMData &problem, std::vector< DoubleReal > &results) | SVMWrapper |  | 
  | predict(const std::vector< svm_node * > &vectors, std::vector< DoubleReal > &predicted_rts) | SVMWrapper |  | 
  | printToVoid_(const char *) | SVMWrapper | privatestatic | 
  | PROBABILITY enum value | SVMWrapper |  | 
  | ProgressLogger() | ProgressLogger |  | 
  | recursion_depth_ | ProgressLogger | protectedstatic | 
  | saveModel(std::string modelFilename) const | SVMWrapper |  | 
  | scaleData(svm_problem *data, Int max_scale_value=-1) | SVMWrapper |  | 
  | setLogType(LogType type) const | ProgressLogger |  | 
  | setParameter(SVM_parameter_type type, Int value) | SVMWrapper |  | 
  | setParameter(SVM_parameter_type type, DoubleReal value) | SVMWrapper |  | 
  | setProgress(SignedSize value) const | ProgressLogger |  | 
  | setTrainingSample(svm_problem *training_sample) | SVMWrapper |  | 
  | setTrainingSample(SVMData &training_sample) | SVMWrapper |  | 
  | setWeights(const std::vector< Int > &weight_labels, const std::vector< DoubleReal > &weights) | SVMWrapper |  | 
  | SIGMA enum value | SVMWrapper |  | 
  | sigma_ | SVMWrapper | private | 
  | sigmas_ | SVMWrapper | private | 
  | startProgress(SignedSize begin, SignedSize end, const String &label) const | ProgressLogger |  | 
  | stop_watch_ | ProgressLogger | mutableprotected | 
  | SVM_kernel_type enum name | SVMWrapper |  | 
  | SVM_parameter_type enum name | SVMWrapper |  | 
  | SVM_TYPE enum value | SVMWrapper |  | 
  | SVMWrapper() | SVMWrapper |  | 
  | train(struct svm_problem *problem) | SVMWrapper |  | 
  | train(SVMData &problem) | SVMWrapper |  | 
  | training_data_ | SVMWrapper | private | 
  | training_problem_ | SVMWrapper | private | 
  | training_set_ | SVMWrapper | private | 
  | type_ | ProgressLogger | mutableprotected | 
  | value_ | ProgressLogger | mutableprotected | 
  | ~ProgressLogger() | ProgressLogger |  | 
  | ~SVMWrapper() | SVMWrapper | virtual |