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Linear causal model discovery using the MML criterion

Li, Gang, Dai, Honghua and Tu, Yiqing 2002, Linear causal model discovery using the MML criterion, in Proceedings of the 2002 IEEE International Conference on Data Mining, IEEE Computer Society, Los Alamitos, Calif., pp. 274-281.

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Title Linear causal model discovery using the MML criterion
Author(s) Li, Gang
Dai, Honghua
Tu, Yiqing
Conference name Institute of Electrical and Electronics Engineers. Conference (2002: Maebishi-shi, Japan)
Conference location Maebishi-shi, Japan
Conference dates 9-12 Dec. 2002
Title of proceedings Proceedings of the 2002 IEEE International Conference on Data Mining
Editor(s) Kumar, Vipin
Tsumoto, S.
Zhong, N.
Yu, P.
Wu, X.
Publication date 2002
Start page 274
End page 281
Publisher IEEE Computer Society
Place of publication Los Alamitos, Calif.
Summary Determining the causal structure of a domain is a key task in the area of Data Mining and Knowledge Discovery.The algorithm proposed by Wallace et al. [15] has demonstrated its strong ability in discovering Linear Causal Models from given data sets. However, some experiments showed that this algorithm experienced difficulty in discovering linear relations with small deviation, and it occasionally gives a negative message length, which should not be allowed. In this paper, a more efficient and precise MML encoding scheme is proposed to describe the model structure and the nodes in a Linear Causal Model. The estimation of different parameters is also derived. Empirical results show that the new algorithm outperformed the previous MML-based algorithm in terms of both speed and precision.
ISBN 0769517544
9780769517544
Language eng
Field of Research 080105 Expert Systems
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ┬ęThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30004875

Document type: Conference Paper
Collections: School of Information Technology
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