BALL::QSAR::GPModel Class Reference

Inheritance diagram for BALL::QSAR::GPModel:

Public Member Functions
Constructors and Destructors

	GPModel (const QSARData &q, int k_type, double p1, double p2=-1)
	GPModel (const QSARData &q, Vector< double > &w)
	GPModel (const QSARData &q, String s1, String s2)
	GPModel (const QSARData &q, const LinearModel &lm, int column)
	~GPModel ()
Accessors

void	train ()
Vector< double >	predict (const vector< double > &substance, bool transform=1)
double	calculateStdErr ()
void	setParameters (vector< double > &v)
vector< double >	getParameters () const
Private Attributes
Attributes

Matrix< double >	L_
Vector< double >	input_
Vector< double >	K_t_
double	lambda_

Detailed Description

class for gaussian process regression

Definition at line 41 of file gpModel.h.

constructor that sets KernelModel.f to s1 and KernelModel.g to s2

BALL::QSAR::GPModel::~GPModel ( )

double BALL::QSAR::GPModel::calculateStdErr ( ) [virtual]

calculates standart error for the last prediction as $\sqrt{k(x_*,x_*)-\sum_{i=1}^n \sum_{j=1}^n k(x_*,x_i)*k(x_*,x_j)-L_{ij} }$

Reimplemented from BALL::QSAR::Model.

vector<double> BALL::QSAR::GPModel::getParameters ( ) const [virtual]

Reimplemented from BALL::QSAR::Model.

Vector<double> BALL::QSAR::GPModel::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.