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learningenv.h

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#ifndef __NEURALENV__
#define __NEURALENV__

#include <nhp/gaenvrnmt.h>
#include <inanna/patternset.h>

// Externals
class PatternSet;
template<class K, class V> class Map;
//typedef Map<String,String> StringMap;

class LearningEAEnv : public EAEnvironment {
    decl_dynamic (LearningEAEnv);
  public:

                        LearningEAEnv   ();
                        LearningEAEnv   (const PatternSet& trainset,
                                         const PatternSet& evaluationset,
                                         const PatternSet& reportset,
                                         StringMap& params);

    void                setProblemType  (int pt) {mProblemType=pt;}

    enum problemtypes {CLASSIFICATION=0, CLASSIFICATION2, APPROXIMATION};
    
    // Implementations

    virtual void        addFeaturesTo   (Genome& genome) const;

    virtual void        cycle_report    (OStream& log, OStream& out);

    virtual double      evaluateg       (const Individual& genome);

    virtual DataOStream& operator>>		(DataOStream& out) const;

    virtual void        check           () const;

  protected:

    void permutate ();

    void                splitTrainData  ();
    Trainer*            createTrainer   () const;
    
  private:
    PatternSet          mTrainData;     // Full training data
    PatternSet          mTrainSet;      // Training part extracted from mTrainData
    PatternSet          mEvaluationSet; // Evaluation part extracted from mTrainData
    const PatternSource& mReportSet;    // Set for "final" testing. Should not even be here.
    StringMap&          mParams;        // Stored application-level parameters, hmmmmm....
    int                 mProblemType;   // classif./2-classif./approx.
    double              mEvalPart;      // Part of training data used for evaluation
    double              mTermPart;      // Part of training data used for termination
    int                 mMaxTrainCycles;// Max number of cycles to train
    int                 mReportCycles;  // Max number of cycles to train for report set
    int                 mValidInterval; // Training termination check interval
    String              mTermMethod;    // Termination method name (default=UP2)
    bool                mPermutate;     // Permutate training data during evolution
};

#endif

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