Feature selection

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In feature selection we are interested in finding the smallest set of features that describes the full data most accurately. Finding it is a combination of a search algorithm for features with an evaluation algorithm for the quality of those features. We discuss two heuristics methods for this problem: the forward and backward selection. We also discuss the example of the Iris dataset.

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