Presentation 1994/7/23
A Note on Inductive Learning of Probabilistic Model
Shinji Abe, Takafumi Mukouchi, Toshiyasu Matsushima, Shigeichi Hirasawa,
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Abstract(in English) This paper discusses an inductive learning method in probabilistic model which is applied to diagnostic system.In this system empirical knowledge is learned from given data as the probability distribution of the failures,and tests are selected according to this knowledge.We use presumption tree to represent the probability distribution,and adopt the MDL principle to select a presumption tree as themost approximate one.But,since the probability distribution becomes complicated,complexity of model selection increases exponentially with number of attributes So it requires an effcient search technique. In this paper,we propose a new effcient algorithm to search the optimal presumption tree which minimize it′s description length.An d we show that our algorithm gives a supplement of the weakness of the conventional algorithm.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Inductive Learning / Minimum Entropy Technique / Presumption Tree / MDL Principle
Paper # IT94-43
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Committee IT
Conference Date 1994/7/23(1days)
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Registration To Information Theory (IT)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Note on Inductive Learning of Probabilistic Model
Sub Title (in English)
Keyword(1) Inductive Learning
Keyword(2) Minimum Entropy Technique
Keyword(3) Presumption Tree
Keyword(4) MDL Principle
1st Author's Name Shinji Abe
1st Author's Affiliation Department of Industrial Engineering and Management,School of Science and Engineering,Waseda University()
2nd Author's Name Takafumi Mukouchi
2nd Author's Affiliation Department of Industrial Engineering and Management,School of Science and Engineering,Waseda University
3rd Author's Name Toshiyasu Matsushima
3rd Author's Affiliation Department of Industrial Engineering and Management,School of Science and Engineering,Waseda University
4th Author's Name Shigeichi Hirasawa
4th Author's Affiliation Department of Industrial Engineering and Management,School of Science and Engineering,Waseda University
Date 1994/7/23
Paper # IT94-43
Volume (vol) vol.94
Number (no) 171
Page pp.pp.-
#Pages 6
Date of Issue