Abstract
As mentioned in Chap. 1, rule generation can be done through the use of the two approaches: divide and conquer and separate and conquer. This chapter describes the two approaches of rule generation. In particular, the existing rule learning algorithms, namely ID3, Prism and Information Entropy Based Rule Generation (IEBRG), are illustrated in detail. These algorithms are also discussed comparatively with respects to their advantages and disadvantages.
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Liu, H., Gegov, A., Cocea, M. (2016). Generation of Classification Rules. In: Rule Based Systems for Big Data. Studies in Big Data, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-23696-4_3
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DOI: https://doi.org/10.1007/978-3-319-23696-4_3
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