featureSelection.h

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// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//

#ifndef BALL_QSAR_FEATURESELECTION_H
#define BALL_QSAR_FEATURESELECTION_H

#ifndef BALL_QSAR_MODEL_H
#include <BALL/QSAR/Model.h>
#endif

#ifndef BALL_QSAR_KERNELMODEL_H
#include <BALL/QSAR/kernelModel.h>
#endif

#ifndef BALL_QSAR_LINEARMODEL_H
#include <BALL/QSAR/linearModel.h>
#endif

#include <set>

namespace BALL 
{
  namespace QSAR
  {

    class BALL_EXPORT FeatureSelection
    {
      public:
        FeatureSelection(Model& m);
        
        FeatureSelection(KernelModel& m);

        ~FeatureSelection();

        EIGEN_MAKE_ALIGNED_OPERATOR_NEW
        
        
        void setModel(Model& m);
        
        void setModel(KernelModel& km);
  
        void forwardSelection(int k=4, bool optPar=0);
        
        void backwardSelection(int k=4, bool optPar=0);
        
        void stepwiseSelection(int k=4, bool optPar=0);
        
        void twinScan(int k, bool optPar=0);
        
        void implicitSelection(LinearModel& lm, int act=1, double d=1);
        
        void removeHighlyCorrelatedFeatures(double& cor_threshold);
        
        
        void removeLowResponseCorrelation(double& min_correlation);
        
        
        void removeEmptyDescriptors();
        
        void selectStat(int s);
        
        void setQualityIncreaseCutoff(double& d);
  
  
      private:
        
        void updateWeights(std::multiset<unsigned int>& oldDescIDs, std::multiset<unsigned int>& newDescIDs, Eigen::VectorXd& oldWeights);
        
        
        std::multiset<unsigned int>* findIrrelevantDescriptors();
        
        Model* model_;
        
        Eigen::VectorXd* weights_;
        
        void forward(bool stepwise, int k, bool optPar);
        
        double quality_increase_cutoff_;
    };
  }
}


#endif // FEATURESEL