31 #ifndef GRT_REGRESSIFIER_HEADER
32 #define GRT_REGRESSIFIER_HEADER
35 #include "../DataStructures/ClassificationData.h"
36 #include "../DataStructures/TimeSeriesClassificationData.h"
40 #define DEFAULT_NULL_LIKELIHOOD_VALUE 0
41 #define DEFAULT_NULL_DISTANCE_VALUE 0
71 bool copyBaseVariables(
const Regressifier *regressifier);
93 std::string getRegressifierType()
const;
127 static Regressifier* createInstanceFromString(
const std::string ®ressifierType );
177 std::string regressifierType;
182 static StringRegressifierMap *getMap() {
183 if( !stringRegressifierMap ){ stringRegressifierMap =
new StringRegressifierMap; }
184 return stringRegressifierMap;
188 static StringRegressifierMap *stringRegressifierMap;
189 static UINT numRegressifierInstances;
194 template<
typename T >
Regressifier *newRegressionModuleInstance() {
return new T; }
196 template<
typename T >
200 getMap()->insert( std::pair< std::string,
Regressifier*(*)() >(newRegresionModuleName, &newRegressionModuleInstance< T > ) );
206 #endif //GRT_REGRESSIFIER_HEADER
bool saveBaseSettingsToFile(std::fstream &file) const
std::map< std::string, Regressifier *(*)() > StringRegressifierMap
virtual bool train(ClassificationData trainingData)
virtual bool deepCopyFrom(const Regressifier *regressifier)
This is the main base class that all GRT machine learning algorithms should inherit from...
bool loadBaseSettingsFromFile(std::fstream &file)