#include <BALL/QSAR/oplsModel.h>
|
| RegressionValidation * | validation |
| |
| const QSARData * | data |
| |
| Validation * | model_val |
| |
| void | calculateOffsets () |
| |
| void | readDescriptorInformationFromFile (std::ifstream &in, int no_descriptors, bool transformation, int no_coefficients) |
| |
| void | saveDescriptorInformationToFile (std::ofstream &out) |
| |
| void | readMatrix (Eigen::MatrixXd &mat, std::ifstream &in, unsigned int lines, unsigned int col) |
| |
| void | readVector (Eigen::RowVectorXd &vec, std::ifstream &in, unsigned int no_cells, bool column_vector) |
| |
| void | readModelParametersFromFile (std::ifstream &in) |
| |
| void | saveModelParametersToFile (std::ofstream &out) |
| |
| virtual void | readDescriptorInformationFromFile (std::ifstream &in, int no_descriptors, bool transformation) |
| |
| void | readResponseTransformationFromFile (std::ifstream &in, int no_y) |
| |
| void | saveResponseTransformationToFile (std::ofstream &out) |
| |
| Eigen::VectorXd | getSubstanceVector (const vector< double > &substance, bool transform) |
| |
| Eigen::VectorXd | getSubstanceVector (const Eigen::VectorXd &substance, bool transform) |
| |
| void | backTransformPrediction (Eigen::VectorXd &pred) |
| |
| void | addLambda (Eigen::MatrixXd &matrix, double &lambda) |
| |
| void | readDescriptorInformation () |
| |
| Eigen::MatrixXd | U_ |
| |
| int | no_components_ |
| |
| Eigen::MatrixXd | training_result_ |
| |
| Eigen::RowVectorXd | offsets_ |
| |
| int | default_no_opt_steps_ |
| |
| Eigen::MatrixXd | descriptor_matrix_ |
| |
| vector< string > | substance_names_ |
| |
| vector< string > | descriptor_names_ |
| |
| Eigen::MatrixXd | descriptor_transformations_ |
| |
| Eigen::MatrixXd | y_transformations_ |
| |
| Eigen::MatrixXd | Y_ |
| |
| String | type_ |
| |
| std::multiset< unsigned int > | descriptor_IDs_ |
| |
| Eigen::MatrixXd | latent_variables_ |
| |
| Eigen::MatrixXd | loadings_ |
| |
| Eigen::MatrixXd | weights_ |
| |
Definition at line 19 of file oplsModel.h.
◆ OPLSModel()
| BALL::QSAR::OPLSModel::OPLSModel |
( |
const QSARData & |
q | ) |
|
◆ ~OPLSModel()
| BALL::QSAR::OPLSModel::~OPLSModel |
( |
| ) |
|
◆ getNoOrthoComponents()
| int BALL::QSAR::OPLSModel::getNoOrthoComponents |
( |
| ) |
|
◆ getParameters()
| vector<double> BALL::QSAR::OPLSModel::getParameters |
( |
| ) |
const |
|
virtual |
◆ getTOrtho()
| const Eigen::MatrixXd* BALL::QSAR::OPLSModel::getTOrtho |
( |
| ) |
|
◆ getWOrtho()
| const Eigen::MatrixXd* BALL::QSAR::OPLSModel::getWOrtho |
( |
| ) |
|
◆ optimizeParameters()
| bool BALL::QSAR::OPLSModel::optimizeParameters |
( |
int |
k, |
|
|
int |
no_steps |
|
) |
| |
|
virtual |
Tries to find the optimal number of PLS components (latente variables) for the current data of this model
Reimplemented from BALL::QSAR::PLSModel.
◆ setNoOrthoComponents()
| void BALL::QSAR::OPLSModel::setNoOrthoComponents |
( |
int |
d | ) |
|
◆ setParameters()
| void BALL::QSAR::OPLSModel::setParameters |
( |
vector< double > & |
| ) |
|
|
virtual |
sets the model parameters according to the given values.
Reimplemented from BALL::QSAR::Model.
◆ train()
| void BALL::QSAR::OPLSModel::train |
( |
| ) |
|
|
virtual |
Starts orthogonal partial least squares regression.
In order to find the optimal number of latente variables for the current data of this model, run findNoLatenteVariables() first.
Reimplemented from BALL::QSAR::PLSModel.