Learning from Cases for Classification Problem Solving
作者： Frank Puppe
DOI: 10.1007/978-3-642-46808-7_4
关键词: Expert system 、 Machine learning 、 Artificial intelligence 、 Bayesian network 、 Problem solver 、 Research areas 、 Computer science
摘要: An overview of case-based learning techniques for classification problem solving from the research areas expert systems, statistics, and neuronal nets is presented, to gether with some results comparative evalutions. We broadly define a solver to be able "learn cases" if it usually performs better every new case.
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