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ICML
1999
IEEE
14 years 8 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
BMCBI
2006
129views more  BMCBI 2006»
13 years 7 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer
COLING
2002
13 years 7 months ago
Data-driven Classification of Linguistic Styles in Spoken Dialogues
Language users have individual linguistic styles. A spoken dialogue system may benefit from adapting to the linguistic style of a user in input analysis and output generation. To ...
Thomas Portele
ICMLA
2010
13 years 5 months ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
IJCV
2006
161views more  IJCV 2006»
13 years 7 months ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert