Rule-based Machine Learning Methods for Functional Prediction
- 1 December 1995
- journal article
- research article
- Published by AI Access Foundation in Journal of Artificial Intelligence Research
- Vol. 3, 383-403
- https://doi.org/10.1613/jair.199
Abstract
We describe a machine learning method for predicting the value of a real-valued function, given the values of multiple input variables. The method induces solutions from samples in the form of ordered disjunctive normal form (DNF) decision rules. A central objective of the method and representation is the induction of compact, easily interpretable solutions. This rule-based decision model can be extended to search efficiently for similar cases prior to approximating function values. Experimental results on real-world data demonstrate that the new techniques are competitive with existing machine learning and statistical methods and can sometimes yield superior regression performance.This publication has 6 references indexed in Scilit:
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