#include <BALL/QSAR/allModel.h>

Inheritance diagram for BALL::QSAR::ALLModel:

Public Member Functions
Constructors and Destructors
	ALLModel (const QSARData &q, double kw=4)

	~ALLModel ()

Public Member Functions inherited from BALL::QSAR::NonLinearModel
	NonLinearModel (const QSARData &q)

	~NonLinearModel ()

Public Member Functions inherited from BALL::QSAR::RegressionModel
	RegressionModel (const QSARData &q)

	~RegressionModel ()

virtual EIGEN_MAKE_ALIGNED_OPERATOR_NEW void	operator= (const RegressionModel &m)

const Eigen::MatrixXd *	getTrainingResult () const

void	show ()

Public Member Functions inherited from BALL::QSAR::Model
	Model (const QSARData &q)

virtual	~Model ()

virtual void	operator= (const Model &m)

void	copyData (const Model &m)

void	copyDescriptorIDs (const Model &m)

void	readTrainingData ()

void	deleteDescriptorIDs ()

bool	optimizeParameters (int k)

virtual double	calculateStdErr ()

std::multiset< unsigned int > *	getDescriptorIDs ()

void	setDataSource (const QSARData *q)

const Eigen::MatrixXd *	getDescriptorMatrix ()

const vector< string > *	getSubstanceNames ()

const vector< string > *	getDescriptorNames ()

const Eigen::MatrixXd	getDescriptorTransformations ()

const Eigen::MatrixXd	getYTransformations ()

const Eigen::MatrixXd *	getY ()

void	setDescriptorIDs (const std::multiset< unsigned int > &sl)

const string *	getType ()

void	getUnnormalizedFeatureValue (int compound, int feature, double &return_value)

void	getUnnormalizedResponseValue (int compound, int response, double &return_value)

Protected Attributes
Attributes
double	kw_

double	lambda_

Protected Attributes inherited from BALL::QSAR::RegressionModel
Eigen::MatrixXd	training_result_

Eigen::RowVectorXd	offsets_

Protected Attributes inherited from BALL::QSAR::Model
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_

Accessors
void	setKw (double kw)

virtual Eigen::VectorXd	predict (const vector< double > &substance, bool transform=1)

void	train ()

virtual bool	optimizeParameters (int d, int no_steps)

double	getKw ()

virtual void	setParameters (vector< double > &v)

virtual vector< double >	getParameters () const

void	saveToFile (string filename)

void	readFromFile (string filename)

virtual void	calculateWeights (Eigen::MatrixXd &dist, Eigen::VectorXd &w)

void	calculateXX (Eigen::VectorXd &w, Eigen::MatrixXd &res)

void	calculateXY (Eigen::VectorXd &w, Eigen::MatrixXd &res)

void	calculateEuclDistanceMatrix (Eigen::MatrixXd &m1, Eigen::MatrixXd &m2, Eigen::MatrixXd &output)

Additional Inherited Members
Public Attributes inherited from BALL::QSAR::RegressionModel
RegressionValidation *	validation

Public Attributes inherited from BALL::QSAR::Model
const QSARData *	data

Validation *	model_val

Protected Member Functions inherited from BALL::QSAR::NonLinearModel
virtual void	calculateOffsets ()

Protected Member Functions inherited from BALL::QSAR::RegressionModel
void	readDescriptorInformationFromFile (std::ifstream &in, int no_descriptors, bool transformation, int no_coefficients)

void	saveDescriptorInformationToFile (std::ofstream &out)

Protected Member Functions inherited from BALL::QSAR::Model
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 ()

Detailed Description

class for automated lazy learning (ALL-QSAR)

Definition at line 20 of file allModel.h.

Constructor & Destructor Documentation

BALL::QSAR::ALLModel::ALLModel	(	const QSARData &	q,
		double	kw = `4`
	)

BALL::QSAR::ALLModel::~ALLModel ( )

Member Function Documentation

void BALL::QSAR::ALLModel::calculateEuclDistanceMatrix	(	Eigen::MatrixXd &	m1,
		Eigen::MatrixXd &	m2,
		Eigen::MatrixXd &	output
	)

protected

calculates pairwise euclidean distance between all substances of m1 and m2 and saves them to Eigen::MatrixXd output

virtual void BALL::QSAR::ALLModel::calculateWeights	(	Eigen::MatrixXd &	dist,
		Eigen::VectorXd &	w
	)

protectedvirtual

Reimplemented in BALL::QSAR::KNNModel.

void BALL::QSAR::ALLModel::calculateXX	(	Eigen::VectorXd &	w,
		Eigen::MatrixXd &	res
	)

protected

calculates weighted Eigen::MatrixXd X^T*X

void BALL::QSAR::ALLModel::calculateXY	(	Eigen::VectorXd &	w,
		Eigen::MatrixXd &	res
	)

protected

calculates weighted Eigen::MatrixXd X^T*Y

double BALL::QSAR::ALLModel::getKw ( )

returns the current kernel width

virtual vector<double> BALL::QSAR::ALLModel::getParameters ( ) const

virtual

Reimplemented from BALL::QSAR::Model.

Reimplemented in BALL::QSAR::KNNModel.

virtual bool BALL::QSAR::ALLModel::optimizeParameters	(	int	d,
		int	no_steps
	)

virtual

Tries to find the optimal kernel width for the current data. Therefore some training data must have been read by the connected QSARData object before running this method.

Reimplemented from BALL::QSAR::Model.

Reimplemented in BALL::QSAR::KNNModel.

virtual Eigen::VectorXd BALL::QSAR::ALLModel::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.