GURU 发表于 2025-3-21 16:50:09
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eving this lofty goal is not easy. First, “long enough” may, in practice, be “too long” in many applications and thus unacceptable. Second, to get “confession” from large data sets one needs to use state-of-the-art “torturing” tools. Third, Nature is very stubborn — not yielding easily or unwillinghandle 发表于 2025-3-22 05:44:47
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F. C. Breedveld,P. L. J. Dautzenberg,S. A. Duursma,Sj. van der Linden,K. Postema,R. A. C. Roos,F. Eujor shortcomings of decision trees have been pointed out: (1) instability, and (2) high computational cost. These problems have been addressed to some extent through ensemble learning techniques such as Random Forest. Unlike decision trees where the whole attribute space of a dataset is used to discAccomplish 发表于 2025-3-23 06:36:06
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