Learning classification rules using lattices (Extended abstract)
作者： Mehran Sahami
关键词:
摘要: This paper presents a novel induction algorithm, Rulearner, which induces classification rules using Galois lattice as an explicit map through the search space of rules. The Rulearner system is shown to compare favorably with commonly used symbolic learning methods use heuristics rather than guide their rule space. Furthermore, our be robust in presence noisy data. also capable both decision lists and unordered sets allowing for comparisons these different paradigms within same algorithmic framework.
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sci-hub.st 参考文章(8)
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