, including all inherited members.
| begin_ | ProgressLogger | [mutable, protected] |
| 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 | [mutable, protected] |
| end_ | ProgressLogger | [mutable, protected] |
| 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 | [mutable, protected] |
| 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 | [private, static] |
| PROBABILITY enum value | SVMWrapper | |
| ProgressLogger() | ProgressLogger | |
| recursion_depth_ | ProgressLogger | [protected, static] |
| 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 | [mutable, protected] |
| 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 | [mutable, protected] |
| value_ | ProgressLogger | [mutable, protected] |
| ~ProgressLogger() | ProgressLogger | |
| ~SVMWrapper() | SVMWrapper | [virtual] |