A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data-Reference-Cited by-同舟云学术

A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data

Published:2018-08-22 Issue:2 Volume:108 Page:229-266
ISSN:0885-6125
Container-title:Machine Learning
language:en
Short-container-title:Mach Learn

Author:

Boullé Marc,Charnay Clément,Lachiche Nicolas^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/article/10.1007/s10994-018-5746-9/fulltext.html

Reference48 articles.

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4. Boullé, M. (2005). A Bayes optimal approach for partitioning the values of categorical attributes. Journal of Machine Learning Research, 6, 1431–1452.

5. Boullé, M. (2006). MODL: A Bayes optimal discretization method for continuous attributes. Machine Learning, 65(1), 131–165.

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