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» Boosted Optimization for Network Classification
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BMCBI
2006
202views more  BMCBI 2006»
14 years 9 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
EOR
2007
108views more  EOR 2007»
14 years 9 months ago
Measuring retail company performance using credit scoring techniques
This paper proposes a theoretical framework for predicting financial distress based on Hunt’s (2000) Resource-Advantage Theory of Competition. The study focuses on the US retail...
Yu-Chiang Hu, Jake Ansell
84
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AAAI
2008
14 years 12 months ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong
FLAIRS
2008
14 years 12 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
CVPR
2004
IEEE
15 years 11 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman