Interpretable Random Forests via Rule Extraction

29 Apr 2020Clément BénardGérard BiauSébastien da VeigaErwan Scornet

We introduce SIRUS (Stable and Interpretable RUle Set) for regression, a stable rule learning algorithm which takes the form of a short and simple list of rules. State-of-the-art learning algorithms are often referred to as ''black boxes'' because of the high number of operations involved in their prediction process... (read more)

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