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Error-Based and Entropy-Based Discretization of Continuous Featuresby: Ron Kohavi, Mehran Sahami
In Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (1996), pp. 114-119.
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AbstractWe present a comparison of error-based and entropybased methods for discretization of continuous features. Our study includes both an extensive empirical comparison as well as an analysis of scenarios where error minimization may be an inappropriate discretization criterion. We present a discretization method based on the C4.5 decision tree algorithm and compare it to an existing entropy-based discretization algorithm, which employs the Minimum Description Length Principle, and a recently...
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