/* Method: ScaleTrainData * * Scales the inputs and outputs in the training data to the specified range. * * A simplified scaling method, which is mostly useful in examples where it's known that all the * data will be in one range and it should be transformed to another range. * * It is not recommended to use this on subsets of data as the complete input range might not be * available in that subset. * * For more powerful scaling, please consider <NeuralNet::ScaleTrain> * * See also: * <ScaleOutputTrainData>, <ScaleInputTrainData>, <fann_scale_train_data at http://libfann.github.io/fann/docs/files/fann_train-h.html#fann_scale_train_data> * * This function appears in FANN >= 2.0.0. */ public void ScaleTrainData(double new_min, double new_max) { InternalData.scale_train_data(new_min, new_max); }
/* Method: ScaleTrainData * * Scales the inputs and outputs in the training data to the specified range. * * A simplified scaling method, which is mostly useful in examples where it's known that all the * data will be in one range and it should be transformed to another range. * * It is not recommended to use this on subsets of data as the complete input range might not be * available in that subset. * * For more powerful scaling, please consider <NeuralNet::ScaleTrain> * * See also: * <ScaleOutputTrainData>, <ScaleInputTrainData>, <fann_scale_train_data at http://libfann.github.io/fann/docs/files/fann_train-h.html#fann_scale_train_data> * * This function appears in FANN >= 2.0.0. */ public void ScaleTrainData(int new_min, int new_max) { InternalData.scale_train_data(new_min, new_max); }