BALL::QSAR::ClassificationValidation Class Reference

#include <BALL/QSAR/classificationValidation.h>

Inheritance diagram for BALL::QSAR::ClassificationValidation:
Inheritance graph
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List of all members.

Public Member Functions

Constructors and Destructors

 ClassificationValidation (ClassificationModel *m)

Private Attributes

Attributes

BALL::Matrix< double > confusion_matrix_
Vector< double > class_results_
double quality_
double quality_input_test_
double quality_cv_
ClassificationModel * clas_model
void(ClassificationValidation::* qualCalculation )()

Accessors



void crossValidation (int k, bool restore=1)
double getCVRes ()
double getFitRes ()
void setCVRes (double d)
void testInputData (bool transform=0)
const BALL::Matrix< double > * getConfusionMatrix ()
const BALL::Vector< double > * getClassResults ()
void bootstrap (int k, bool restore=1)
const BALL::Matrix< double > & yRandomizationTest (int runs, int k)
double getAccuracyCV ()
double getAccuracyInputTest ()
void selectStat (int s)
void saveToFile (string filename) const
void saveToFile (string filename, const double &quality_input_test, const double &predictive_quality) const
void readFromFile (string filename)
void testAllSubstances (bool transform)
void calculateAverageSensitivity ()
void calculateWeightedSensitivity ()
void calculateOverallAccuracy ()
void calculateAverageMCC ()
void calculateOverallMCC ()
void calculateTDR ()

Detailed Description

class for validation of QSAR regression models

Definition at line 48 of file classificationValidation.h.

Constructor & Destructor Documentation

BALL::QSAR::ClassificationValidation::ClassificationValidation ( ClassificationModel *  m  ) 

constructor

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

Member Function Documentation

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

starts bootstrapping with k samples

Parameters:
k no of bootstrap samples

Implements BALL::QSAR::Validation.

void BALL::QSAR::ClassificationValidation::calculateAverageMCC (  )  [private]

calculate one MCC for each class and use the average

void BALL::QSAR::ClassificationValidation::calculateAverageSensitivity (  )  [private]

calculate average accuracy with the current values of TP, FP, FN, TN in matrix ClassificationValidation.predictions.

void BALL::QSAR::ClassificationValidation::calculateOverallAccuracy (  )  [private]

calculate accuracy for all classes at once

void BALL::QSAR::ClassificationValidation::calculateOverallMCC (  )  [private]

calculate MCC for all classes at once

void BALL::QSAR::ClassificationValidation::calculateTDR (  )  [private]

calculate the True Discovery Rate (only applicable to binary classification validation results).

void BALL::QSAR::ClassificationValidation::calculateWeightedSensitivity (  )  [private]

calculate weighted average accuracy of all classes. Weighted by the number of training compounds within each class

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

Starts cross-validation with k steps.
Data is taken from QSARData.descriptor_matrix and is in each step divided into training- and test-data.
(Data having already been copied into Model.descriptor_matrix will be deleted)

Implements BALL::QSAR::Validation.

double BALL::QSAR::ClassificationValidation::getAccuracyCV (  ) 

get average accuracy value as determined after cross validation

double BALL::QSAR::ClassificationValidation::getAccuracyInputTest (  ) 

get average accuracy value as determined after testing of input data();

const BALL::Vector<double>* BALL::QSAR::ClassificationValidation::getClassResults (  ) 

returns a RowVector holding the one value contituting the validation result for each class if "average accuracy" or "average MCC" is chosen (see selectStat()).

const BALL::Matrix<double>* BALL::QSAR::ClassificationValidation::getConfusionMatrix (  ) 

return pointer to the matrix containing the number of TP, FP, TN, FN in one column for each class

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

fetches the result of cross-validation

Implements BALL::QSAR::Validation.

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

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

Implements BALL::QSAR::Validation.

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

restore validation-results from a file

Implements BALL::QSAR::Validation.

void BALL::QSAR::ClassificationValidation::saveToFile ( string  filename,
const double &  quality_input_test,
const double &  predictive_quality 
) const
void BALL::QSAR::ClassificationValidation::saveToFile ( string  filename  )  const [virtual]

save the result of the applied validation methods to a file

Implements BALL::QSAR::Validation.

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

set the result of cross-validation to the given value

Implements BALL::QSAR::Validation.

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

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

void BALL::QSAR::ClassificationValidation::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::ClassificationValidation::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 accuracy_input_test and accuracy_cv value to a vector, where BALL::Matrix<double>(i,0)=accuracy_input_test, BALL::Matrix<double>(i,1)=accuracy_cv

Parameters:
runs this is repeated as often as specified by 'runs'

Implements BALL::QSAR::Validation.

Member Data Documentation

ClassificationModel* BALL::QSAR::ClassificationValidation::clas_model [private]

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

Definition at line 148 of file classificationValidation.h.

Vector<double> BALL::QSAR::ClassificationValidation::class_results_ [private]

RowVector holding the one value contituting the validation result for each class if "average sensitivity" or "average MCC" is chosen (see selectStat()).

Definition at line 139 of file classificationValidation.h.

BALL::Matrix<double> BALL::QSAR::ClassificationValidation::confusion_matrix_ [private]

matrix containing the number of TP, FP, FN, TN in one column for each class

Definition at line 136 of file classificationValidation.h.

void(ClassificationValidation::* BALL::QSAR::ClassificationValidation::qualCalculation)() [private]

Definition at line 150 of file classificationValidation.h.

double BALL::QSAR::ClassificationValidation::quality_ [private]

Definition at line 141 of file classificationValidation.h.

double BALL::QSAR::ClassificationValidation::quality_cv_ [private]

Definition at line 145 of file classificationValidation.h.

double BALL::QSAR::ClassificationValidation::quality_input_test_ [private]

Definition at line 143 of file classificationValidation.h.

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