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| | NBModel (const QSARData &q) |
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| | ~NBModel () |
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| void | train () |
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| Eigen::VectorXd | predict (const vector< double > &substance, bool transform=1) |
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| void | saveToFile (string filename) |
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| void | readFromFile (string filename) |
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| vector< double > | getParameters () const |
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| void | setParameters (vector< double > &v) |
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| bool | isTrained () |
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| vector< double > | calculateProbabilities (int activitiy_index, int feature_index, double feature_value) |
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| int | getNoResponseVariables () |
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| | BayesModel (const QSARData &q) |
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| virtual bool | isTrained ()=0 |
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| virtual vector< double > | calculateProbabilities (int activitiy_index, int feature_index, double feature_value)=0 |
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| virtual int | getNoResponseVariables ()=0 |
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| | ClassificationModel (const QSARData &q) |
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| | ~ClassificationModel () |
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| virtual void | operator= (ClassificationModel &m) |
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| std::vector< int > | getClassLabels () |
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| | Model (const QSARData &q) |
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| virtual | ~Model () |
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| virtual void | operator= (const Model &m) |
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| void | copyData (const Model &m) |
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| void | copyDescriptorIDs (const Model &m) |
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| void | readTrainingData () |
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| void | deleteDescriptorIDs () |
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| virtual bool | optimizeParameters (int, int) |
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| bool | optimizeParameters (int k) |
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| virtual double | calculateStdErr () |
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| std::multiset< unsigned int > * | getDescriptorIDs () |
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| void | setDataSource (const QSARData *q) |
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| const Eigen::MatrixXd * | getDescriptorMatrix () |
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| const vector< string > * | getSubstanceNames () |
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| const vector< string > * | getDescriptorNames () |
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| const Eigen::MatrixXd | getDescriptorTransformations () |
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| const Eigen::MatrixXd | getYTransformations () |
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| const Eigen::MatrixXd * | getY () |
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| void | setDescriptorIDs (const std::multiset< unsigned int > &sl) |
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| const string * | getType () |
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| void | getUnnormalizedFeatureValue (int compound, int feature, double &return_value) |
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| void | getUnnormalizedResponseValue (int compound, int response, double &return_value) |
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| ClassificationValidation * | validation |
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| const QSARData * | data |
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| Validation * | model_val |
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| void | readClassInformationFromFile (std::ifstream &input, int no_classes) |
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| void | saveClassInformationToFile (std::ofstream &out) |
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| void | readLabels () |
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| void | equalSpaceDiscretization (unsigned int bins, Eigen::MatrixXd &discretization_information) |
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| void | equalSpaceDiscretizationTestData (Eigen::VectorXd &compound, unsigned int bins, const Eigen::MatrixXd &discretization_information) |
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| void | readMatrix (Eigen::MatrixXd &mat, std::ifstream &in, unsigned int lines, unsigned int col) |
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| void | readVector (Eigen::RowVectorXd &vec, std::ifstream &in, unsigned int no_cells, bool column_vector) |
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| void | readModelParametersFromFile (std::ifstream &in) |
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| void | saveModelParametersToFile (std::ofstream &out) |
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| virtual void | saveDescriptorInformationToFile (std::ofstream &out) |
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| virtual void | readDescriptorInformationFromFile (std::ifstream &in, int no_descriptors, bool transformation) |
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| void | readResponseTransformationFromFile (std::ifstream &in, int no_y) |
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| void | saveResponseTransformationToFile (std::ofstream &out) |
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| Eigen::VectorXd | getSubstanceVector (const vector< double > &substance, bool transform) |
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| Eigen::VectorXd | getSubstanceVector (const Eigen::VectorXd &substance, bool transform) |
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| void | backTransformPrediction (Eigen::VectorXd &pred) |
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| void | addLambda (Eigen::MatrixXd &matrix, double &lambda) |
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| void | readDescriptorInformation () |
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| double | min_prob_diff_ |
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| double | undef_act_class_id_ |
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| std::vector< int > | labels_ |
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| std::vector< int > | no_substances_ |
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| void(ClassificationModel::* | discretizeFeatures )(unsigned int bins, Eigen::MatrixXd &discretization_information) |
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| void(ClassificationModel::* | discretizeTestDataFeatures )(Eigen::VectorXd &compound, unsigned int bins, const Eigen::MatrixXd &discretization_information) |
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| int | default_no_opt_steps_ |
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| Eigen::MatrixXd | descriptor_matrix_ |
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| vector< string > | substance_names_ |
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| vector< string > | descriptor_names_ |
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| Eigen::MatrixXd | descriptor_transformations_ |
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| Eigen::MatrixXd | y_transformations_ |
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| Eigen::MatrixXd | Y_ |
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| String | type_ |
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| std::multiset< unsigned int > | descriptor_IDs_ |
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class for Naive Bayes
Definition at line 27 of file nBModel.h.