Finding the optimal cardinality value for information bottleneck method

Li, Gang, Liu, Dong, Tu, Yiqing and Ye, Yangdong 2006, Finding the optimal cardinality value for information bottleneck method, Lecture notes in computer science, vol. 4093, pp. 594-605.

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Title Finding the optimal cardinality value for information bottleneck method
Author(s) Li, GangORCID iD for Li, Gang
Liu, Dong
Tu, Yiqing
Ye, Yangdong
Journal name Lecture notes in computer science
Volume number 4093
Start page 594
End page 605
Publisher Springer-Verlag
Place of publication Berlin, Germany
Publication date 2006
ISSN 0302-9743
Summary Information Bottleneck method can be used as a dimensionality reduction approach by grouping “similar” features together [1]. In application, a natural question is how many “features groups” will be appropriate. The dependency on prior knowledge restricts the applications of many Information Bottleneck algorithms. In this paper we alleviate this dependency by formulating the parameter determination as a model selection problem, and solve it using the minimum message length principle. An efficient encoding scheme is designed to describe the information bottleneck solutions and the original data, then the minimum message length principle is incorporated to automatically determine the optimal cardinality value. Empirical results in the documentation clustering scenario indicates that the proposed method works well for the determination of the optimal parameter value for information bottleneck method.
Language eng
Field of Research 080299 Computation Theory and Mathematics not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2006, Springer-Verlag Berlin Heidelberg
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Document type: Journal Article
Collection: School of Engineering and Information Technology
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