Rule-based Machine Learning Methods for Functional Prediction
<|reference_start|>Rule-based Machine Learning Methods for Functional Prediction: 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.<|reference_end|>
@article{weiss1995rule-based,
    title={Rule-based Machine Learning Methods for Functional Prediction},
    author={S. M. Weiss, N. Indurkhya},
    journal={Journal of Artificial Intelligence Research, Vol 3, (1995),
  383-403},
    year={1995},
    archivePrefix={arXiv},
    eprint={cs/9512107},
    primaryClass={cs.AI}
}