BALL::QSAR::NBModel Class Reference

#include <BALL/QSAR/nBModel.h>

Inheritance diagram for BALL::QSAR::NBModel:

[legend]

List of all members.

Public Member Functions
Constructors and Destructors
	NBModel (const QSARData &q)
	~NBModel ()
Accessors
void	train ()
Vector< double >	predict (const vector< double > &substance, bool transform=1)
void	saveToFile (string filename)
void	readFromFile (string filename)
vector< double >	getParameters () const
void	setParameters (vector< double > &v)
bool	isTrained ()
vector< double >	calculateProbabilities (int activitiy_index, int feature_index, double feature_value)
int	getNoResponseVariables ()
Private Attributes
Attributes
uint	discretization_steps_
Matrix< double >	min_max_
vector< vector< Matrix< double > > >	probabilities_

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Detailed Description

class for Naive Bayes

Definition at line 43 of file nBModel.h.

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Constructor & Destructor Documentation

BALL::QSAR::NBModel::NBModel

(

const QSARData &

q

)

BALL::QSAR::NBModel::~NBModel

(

)

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Member Function Documentation

vector<double> BALL::QSAR::NBModel::calculateProbabilities	(	int	activitiy_index,
		int	feature_index,
		double	feature_value
	)			[virtual]

calculate the probability for the specified feature to assume the given value for each class

Returns:

a probability for each class

Implements BALL::QSAR::BayesModel.

int BALL::QSAR::NBModel::getNoResponseVariables

(

)

[virtual]

returns the number of response variables for which this model has been trained

Implements BALL::QSAR::BayesModel.

vector<double> BALL::QSAR::NBModel::getParameters

(

)

const [virtual]

Reimplemented from BALL::QSAR::Model.

bool BALL::QSAR::NBModel::isTrained

(

)

[virtual]

Implements BALL::QSAR::BayesModel.

Vector<double> BALL::QSAR::NBModel::predict	(	const vector< double > &	substance,
		bool	transform = 1
	)			[virtual]

Predicts the activities of a given substance

Parameters:

	substance	the substance which activity is to be predicted in form of a vecor containing the values for *all* descriptors (if neccessary, relevant descriptors will be selected automatically)
	transform	determines whether the values for each descriptor of the given substance should be transformed before prediction of activity. If (transform==1): each descriptor value is transformed according to the centering of the respective column of QSARData.descriptor_matrix used to train this model. If the substance to be predicted is part of the same input data (e.g. same SD-file) as the training data (as is the case during cross validation), transform should therefore be set to 0.

Returns:

a RowVector containing one value for each predicted activity

Implements BALL::QSAR::Model.

void BALL::QSAR::NBModel::readFromFile

(

string

filename

)

[virtual]

reconstruct a saved Model from a file

Implements BALL::QSAR::Model.

void BALL::QSAR::NBModel::saveToFile

(

string

filename

)

[virtual]

save Model to a file

Implements BALL::QSAR::Model.

void BALL::QSAR::NBModel::setParameters

(

vector< double > &

)

[virtual]

sets the model parameters according to the given values.

Reimplemented from BALL::QSAR::Model.

void BALL::QSAR::NBModel::train

(

)

[virtual]

Starts training the model.

Implements BALL::QSAR::Model.

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Member Data Documentation

uint BALL::QSAR::NBModel::discretization_steps_ [private]

Definition at line 83 of file nBModel.h.

Matrix<double> BALL::QSAR::NBModel::min_max_ [private]

the minmum (row1) and maximum (row2) of each feature.

Definition at line 87 of file nBModel.h.

vector<vector<Matrix<double> > > BALL::QSAR::NBModel::probabilities_ [private]

One probability Matrix for each modelled activity and each class.
Each Matrix stores in each cell the probability for a feature lying within a specific range to be in a specific class

Definition at line 91 of file nBModel.h.