When using decision tree regression, it's not necessary to normalize the training data predictor values because no distance between data items is computed. However, normalizing the predictors doesn't ...

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...