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대한안전경영과학회지
(Journal of Korea Safety Management & Science)
제2권 제3호 (2000.09)
pp.171-184
pp.171-184
대한안전경영과학회
(Korea Safety Management & Science)
초록
We may be given a set of observations with the classes or clusters. The aim of this article is to provide an up-to-date review of different approaches to classification, compare their performance on a wide range of challenging data-sets. In this paper, machine learning algorithm classifiers based on CART, C4.5, CAL5, FACT, QUEST and statistical discriminant analysis are compared on various datasets in classification error rate and algorithms.
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