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// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
//
#ifndef SNBMODEL
#define SNBMODEL
#ifndef BALL_QSAR_COMMON_H
#include <BALL/QSAR/common.h>
#endif
#ifndef STATISTICS
#include <BALL/QSAR/statistics.h>
#endif
#ifndef BAYESMODEL
#include <BALL/QSAR/bayesModel.h>
#endif
namespace BALL{
namespace QSAR {
/** class for simple naive Bayes */
class BALL_EXPORT SNBModel : public BayesModel
{
public:
/** @name Constructors and Destructors
*/
//@{
SNBModel(const QSARData& q);
~SNBModel();
//@}
/** @name Accessors
*/
//@{
void train();
Eigen::VectorXd predict(const vector<double>& substance, bool transform=1);
vector<double> getParameters() const;
void setParameters(vector<double>& v);
void saveToFile(string filename);
bool isTrained();
void readFromFile(string filename);
/** calculate the probability for the specified feature to assume the given value for each class
@return a probability for each class */
vector<double> calculateProbabilities(int activitiy_index, int feature_index, double feature_value);
int getNoResponseVariables();
//@}
private:
/** @name Attributes
*/
//@{
/** vector containing one matrix for each modelled activity which holds the mean of each feature for each class */
MatrixVector mean_;
/** vector containing one matrix for each modelled activity which holds the standard deviation of each feature for each class */
MatrixVector stddev_;
static const double sqrt2Pi_;
//@}
};
}
}
#endif //SNBMODEL
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