BALL::QSAR::RegressionValidation Class Reference

#include <BALL/QSAR/regressionValidation.h>

Inheritance diagram for BALL::QSAR::RegressionValidation:

Classes
struct	BackupData
Public Member Functions
Constructors and Destructors

	RegressionValidation (RegressionModel *m)
	~RegressionValidation ()
Attributes

double	ssR_
double	ssE_
double	ssY_
double	std_err_
double	Q2_
double	F_cv_
double	F_regr_
double	R2_
double	max_error_
double	quality_
double(RegressionValidation::*	predQualFetcher_ )()
double(RegressionValidation::*	fitQualFetcher_ )()
BALL::Matrix< double >	coefficient_stderr_
RegressionModel *	regr_model_
BackupData	backup_data_
void(RegressionValidation::*	qualCalculation )()
void	calculateQOF ()
Accessors

void	crossValidation (int k, bool restore=1)
void	crossValidation (int k, vector< BALL::Matrix< double > > *results, bool restore=1)
void	bootstrap (int k, bool restore=1)
void	bootstrap (int k, vector< BALL::Matrix< double > > *results, bool restore=1)
void	bootstrap1 (int k, vector< BALL::Matrix< double > > *results, bool restore=1)
const BALL::Matrix< double > &	yRandomizationTest (int runs, int k)
double	getQ2 ()
double	getR2 ()
double	getFregr ()
double	getFcv ()
double	getCVRes ()
double	getFitRes ()
double	getMaxError ()
void	setCVRes (double d)
void	setQ2 (double d)
void	testInputData (bool transform=0)
void	selectStat (int s)
void	calculateCoefficientStdErrors (int k, bool b=1)
const BALL::Matrix< double > *	getCoefficientStdErrors ()
void	setCoefficientStdErrors (const BALL::Matrix< double > *stddev)
void	saveToFile (string filename) const
void	saveToFile (string filename, const double &r2, const double &q2, const Matrix< double > &coefficient_stddev, const Matrix< double > &yRand_results) const
void	readFromFile (string filename)
void	testAllSubstances (bool transform)
void	backupTrainingResults ()
void	restoreTrainingResults ()

Detailed Description

class for validation of QSAR regression models

Definition at line 53 of file regressionValidation.h.

Constructor & Destructor Documentation

BALL::QSAR::RegressionValidation::RegressionValidation ( RegressionModel * m )

constructor

Parameters:

m

pointer to the regression model, which the object of this class should test

BALL::QSAR::RegressionValidation::~RegressionValidation ( )

Member Function Documentation

void BALL::QSAR::RegressionValidation::backupTrainingResults ( ) [private]

void BALL::QSAR::RegressionValidation::bootstrap	(	int	k,
		vector< BALL::Matrix< double > > *	results,
		bool	restore = `1`
	)

starts bootstrapping with k samples

Parameters:

	k	no of bootstrap samples
	restore	if restore==1, Model.descriptor_matrix and RegressionModel.training_result is restored after bootstrapping
	results	pointer to vector that should take all matrices RegressionModel.training_result produced during this bootstrapping

void BALL::QSAR::RegressionValidation::bootstrap	(	int	k,
		bool	restore = `1`
	)			`[virtual]`

starts bootstrapping with k samples

Parameters:

	k	no of bootstrap samples
	restore	if restore==1, Model.descriptor_matrix and RegressionModel.training_result is restored after bootstrapping

Implements BALL::QSAR::Validation.

void BALL::QSAR::RegressionValidation::bootstrap1	(	int	k,
		vector< BALL::Matrix< double > > *	results,
		bool	restore = `1`
	)

void BALL::QSAR::RegressionValidation::calculateCoefficientStdErrors	(	int	k,
		bool	b = `1`
	)

calculates standart deviations for all predicted coefficients and saves them to coefficient_stddev_

Parameters:

	b	if b==1, bootstrapping is used; else: cross-validation
	k	number of bootstrap samples resp. cross-validation steps

void BALL::QSAR::RegressionValidation::calculateQOF ( ) [private]

void BALL::QSAR::RegressionValidation::crossValidation	(	int	k,
		vector< BALL::Matrix< double > > *	results,
		bool	restore = `1`
	)

starts k-fold cross validation

Parameters:

	k	no of cross validation folds
	restore	if restore==1, Model.descriptor_matrix and RegressionModel.training_result is restored after cross validation
	results	pointer to vector that should take all matrices RegressionModel.training_result produced during this cross validation run

void BALL::QSAR::RegressionValidation::crossValidation	(	int	k,
		bool	restore = `1`
	)			`[virtual]`

starts k-fold cross validation

Parameters:

	k	no of cross validation folds
	restore	if restore==1, Model.descriptor_matrix and RegressionModel.training_result is restored after cross validation

Implements BALL::QSAR::Validation.

const BALL::Matrix<double>* BALL::QSAR::RegressionValidation::getCoefficientStdErrors ( )

returns a const pointer to the matrix containing the standart deviations of all predicted coefficients

double BALL::QSAR::RegressionValidation::getCVRes ( ) [virtual]

fetches the result of cross-validation

Implements BALL::QSAR::Validation.

double BALL::QSAR::RegressionValidation::getFcv ( )

get the F-value as calculated by cross validation.
If crossValidation() has not been run yet, -1 is returned

double BALL::QSAR::RegressionValidation::getFitRes ( ) [virtual]

fetches the quality of fit to the input data, as calculated by testInputData()

Implements BALL::QSAR::Validation.

double BALL::QSAR::RegressionValidation::getFregr ( )

get the F-value as calculated by testInputData().
If testInputData() has not been run yet, -1 is returned

double BALL::QSAR::RegressionValidation::getMaxError ( )

returns the maximal error of the prediction

double BALL::QSAR::RegressionValidation::getQ2 ( )

get the Q^2 value.
If no cross-validation has been done yet, -1 is returned

double BALL::QSAR::RegressionValidation::getR2 ( )

get the R^2 value.
If testInputData() has not been run yet, -1 is returned

void BALL::QSAR::RegressionValidation::readFromFile ( string filename ) [virtual]

restore validation-results from a file

Implements BALL::QSAR::Validation.

void BALL::QSAR::RegressionValidation::restoreTrainingResults ( ) [private]

void BALL::QSAR::RegressionValidation::saveToFile	(	string	filename,
		const double &	r2,
		const double &	q2,
		const Matrix< double > &	coefficient_stddev,
		const Matrix< double > &	yRand_results
	)			const

void BALL::QSAR::RegressionValidation::saveToFile ( string filename ) const [virtual]

save the result of the applied validation methods to a file

Implements BALL::QSAR::Validation.

void BALL::QSAR::RegressionValidation::selectStat ( int s ) [virtual]

select the desired statistic to be used for validating the models

Parameters:

s

if (s==1) R^2 and Q^2 are used
if(s==2) F_regr and F_cv are used.

Implements BALL::QSAR::Validation.

void BALL::QSAR::RegressionValidation::setCoefficientStdErrors ( const BALL::Matrix< double > * stddev )

void BALL::QSAR::RegressionValidation::setCVRes ( double d ) [virtual]

set the result of cross-validation to the given value

Implements BALL::QSAR::Validation.

void BALL::QSAR::RegressionValidation::setQ2 ( double d )

set the Q^2 value

void BALL::QSAR::RegressionValidation::testAllSubstances ( bool transform ) [private]

Tests the current model with all substances in the (unchanged) test data set

void BALL::QSAR::RegressionValidation::testInputData ( bool transform = 0 ) [virtual]

Fetches input data from QSARData and tests the current (unchanged) model with all these new substances (without cross-validation!).

Parameters:

transform

if transform==1, the test data is transformed in the same way that the training data was transformed before predicting activities.
If training and test substances are taken from the same input file, set transform to 0

Implements BALL::QSAR::Validation.

const BALL::Matrix<double>& BALL::QSAR::RegressionValidation::yRandomizationTest	(	int	runs,
		int	k
	)			`[virtual]`

Y randomization test
Randomizes all columns of model.Y, trains the model, runs crossValidation and testInputData and saves the resulting R2 and Q2 value to a matrix with 2 columns; the R2 values makeing up the first colum, the Q2 value the second.

Parameters:

runs

this is repeated as often as specified by 'runs'

Implements BALL::QSAR::Validation.