startup(file, train, dialog.getMaxError().getValue() / 100.0);
}
}
private void performManhattan(ProjectEGFile file, MLDataSet trainingData) {
InputManhattan dialog = new InputManhattan();
if (dialog.process()) {
double learningRate = dialog.getFixedDelta().getValue();
int kFold = dialog.getKfold().getValue();
if( kFold>0 ) {
trainingData = this.wrapTrainingData(trainingData);
}
MLTrain train = new ManhattanPropagation(
(BasicNetwork) file.getObject(), trainingData, learningRate);
if( kFold>0 ) {
train = this.wrapTrainer(trainingData,train,kFold);
}
startup(file, train, dialog.getMaxError().getValue() / 100.0);
}
}