A global optimal algorithm for class-dependent discretization of continuous data

Abstract

This paper presents a new method to convert continuous variables into discrete variables for inductive machine learning. The method can be applied to pattern classification problems in machine learning and data mining. The discretization process is formulated as an optimization problem. We first use the normalized mutual information that measures the… (More)

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@article{Liu2004AGO, title={A global optimal algorithm for class-dependent discretization of continuous data}, author={Lili Liu and Andrew K. C. Wong and Yang Wang}, journal={Intell. Data Anal.}, year={2004}, volume={8}, pages={151-170} }