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# 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.
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