# Preprocessing / feature extraction mlpack provides a number of utilities for data preparation and feature extraction. These utilities are generally used just before actually applying any machine learning [transformations](transformations.md) or [modeling](modeling.md). *Note: this section is under construction and not all functionality is documented yet.* * [Normalizing labels](core/normalizing_labels.md): convert labels to/from an arbitrary range to `[0, numClasses - 1]`, which is the range that mlpack classifiers require. * [Dataset splitting](core/split.md): split a dataset into a training and test set, optionally including labels.