作者： Yves Kodratoff , Derek Sleeman , Marc Uszynski , Karine Causse , Susan Craw
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摘要: This paper presents the results of the ESPRIT project" Machine Learning Toolbox"(MLT), as well as some of its problems. It describes the place of MLT in contemporary research, and shows that machine learning can be applied to a variety of real-life problems. The paper gives details of the organization of MLT, its algorithms, its Consultant helping to choose the best suited algorithm, and its common knowledge representation language.