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arXiv · 1807.04602

Rule Induction Partitioning Estimator

Vincent Margot·Jean-Patrick Baudry·Frederic Guilloux·Olivier Wintenberger
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Abstract

RIPE is a novel deterministic and easily understandable prediction algorithm developed for continuous and discrete ordered data. It infers a model, from a sample, to predict and to explain a real variable $Y$ given an input variable $X \in \mathcal X$ (features). The algorithm extracts a sparse set of hyperrectangles $\mathbf r \subset \mathcal X$, which can be thought of as rules of the form If-Then. This set is then turned into a partition of the features space $\mathcal X$ of which each cell is explained as a list of rules with satisfied their If conditions. The process of RIPE is illustrated on simulated datasets and its efficiency compared with that of other usual algorithms.

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Vincent Margot, Jean-Patrick Baudry, Frederic Guilloux, Olivier Wintenberger. 2018-07-12. Rule Induction Partitioning Estimator. https://arxiv.org/abs/1807.04602

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