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 or modeling.
Note: this section is under construction and not all functionality is documented yet.
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Normalizing labels: convert labels to/from an arbitrary range to
[0, numClasses - 1], which is the range that mlpack classifiers require. -
Dataset splitting: split a dataset into a training and test set, optionally including labels.