# Rule Induction Partitioning Estimator

arXiv: https://arxiv.org/abs/1807.04602 · HTML: https://mlsanity.com/paper/1807.04602/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jul 2018.

## Built on by (most cited first, 1 of 1)

- [Making use of supercomputers in financial machine learning](https://mlsanity.com/paper/2203.00427/) (2022)

## Abstract (arXiv)

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 ∈ 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.