Presentation 1997/4/26
Interactive Bayesian Structural Modeling : An Integrated Approach for Constructiong Causal Structure from Data
Hitoshi Ohnishi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, I propose an interactive method for constructing Bayesian networks from data. The proposed method constructs Bayesian networks by an integrated approach of automatic construction (learning) of Bayesian networks from data and diagrammatic reasoning (reasoning with diagrammatic information). After obtain the initial Bayesian network by the automatic Bayesian network constructor, hierarchical structure of the network is displayed using Interactive Structural Modeling (ISM) method. Visual information enables user to notice inappropriate arcs (e.g. those that violate causal laws), irrelevant variables, and features of the structure. Therefore, user can provide the automatic Bayesian network constructor with new information that helps it to construct elaborated networks. User cannot only obtain elaborated networks but also understand the system by repeating these interactive processes. Moreover, the proposed method was applied to real data. The result showed that the proposed method can construct plausible models even if the size of samples is small.
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Keyword(in English) Bayesian network / causal structure / diagrammatic reasoning / ISM
Paper # ET97-6
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Conference Date 1997/4/26(1days)
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Registration To Educational Technology (ET)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Interactive Bayesian Structural Modeling : An Integrated Approach for Constructiong Causal Structure from Data
Sub Title (in English)
Keyword(1) Bayesian network
Keyword(2) causal structure
Keyword(3) diagrammatic reasoning
Keyword(4) ISM
1st Author's Name Hitoshi Ohnishi
1st Author's Affiliation National Institute of Multimedia Education()
Date 1997/4/26
Paper # ET97-6
Volume (vol) vol.97
Number (no) 33
Page pp.pp.-
#Pages 8
Date of Issue