9 #ifndef GRT_TRAINING_RESULT_HEADER
10 #define GRT_TRAINING_RESULT_HEADER
25 trainingMode = CLASSIFICATION_MODE;
26 trainingIteration = 0;
28 totalSquaredTrainingError = 0;
29 rootMeanSquaredTrainingError = 0;
60 this->trainingMode = rhs.trainingMode;
61 this->trainingIteration = rhs.trainingIteration;
62 this->accuracy = rhs.accuracy;
63 this->totalSquaredTrainingError = rhs.totalSquaredTrainingError;
64 this->rootMeanSquaredTrainingError = rhs.rootMeanSquaredTrainingError;
65 this->trainer = rhs.trainer;
85 return trainingIteration;
105 return totalSquaredTrainingError;
115 return rootMeanSquaredTrainingError;
136 this->trainingMode = CLASSIFICATION_MODE;
137 this->trainingIteration = trainingIteration;
138 this->accuracy = accuracy;
139 this->trainer = trainer;
152 bool setRegressionResult(
unsigned int trainingIteration,
double totalSquaredTrainingError,
double rootMeanSquaredTrainingError,
MLBase *trainer){
153 this->trainingMode = REGRESSION_MODE;
154 this->trainingIteration = trainingIteration;
155 this->totalSquaredTrainingError = totalSquaredTrainingError;
156 this->rootMeanSquaredTrainingError = rootMeanSquaredTrainingError;
157 this->trainer = trainer;
163 unsigned int trainingMode;
164 unsigned int trainingIteration;
166 double totalSquaredTrainingError;
167 double rootMeanSquaredTrainingError;
172 enum TrainingMode{CLASSIFICATION_MODE=0,REGRESSION_MODE};
178 #endif //GRT_TRAINING_RESULT_HEADER
bool setRegressionResult(unsigned int trainingIteration, double totalSquaredTrainingError, double rootMeanSquaredTrainingError, MLBase *trainer)
double getTotalSquaredTrainingError() const
double getAccuracy() const
TrainingResult & operator=(const TrainingResult &rhs)
unsigned int getTrainingIteration() const
MLBase * getTrainer() const
double getRootMeanSquaredTrainingError() const
bool setClassificationResult(unsigned int trainingIteration, double accuracy, MLBase *trainer)
unsigned int getTrainingMode() const
TrainingResult(const TrainingResult &rhs)