Classification Functions for Machine Learning and Data Mining
Introduction.- Definitions and Basic Properties.- Minimization of Variables: Exact Method.- Minimization of Variables: Heuristic Method.- Two-Class Functions.- Linear Decomposition.- Data Mining and Machine Learning.- Functions with Multi-Valued Inputs.- Easily Reconstructable Functions.- Functions with Continuous Variables.- References.- Conclusions.
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Sasao, Tsutomu
Tsutomu Sasao received B.E., M.E., and Ph.D. degrees in Electronics Engineering from Osaka University, Osaka Japan, in 1972, 1974, and 1977, respectively. He has held faculty/research positions at Osaka University, Japan; IBM T. J. Watson Research Center, Yorktown Height, NY; the Naval Postgraduate School, Monterey, CA; Kyushu Institute of Technology, Japan; and Meiji University, Kawasaki, Japan. Currently, he is a visiting researcher of Meiji University, Japan. He is a Life Fellow of the IEEE, and has published many books on logic design.
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