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» Variable selection using neural-network models
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BMCBI
2008
139views more  BMCBI 2008»
14 years 9 months ago
The C1C2: A framework for simultaneous model selection and assessment
Background: There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper m...
Martin Eklund, Ola Spjuth, Jarl E. S. Wikberg
ICDAR
2007
IEEE
15 years 1 months ago
On the Use of Lexeme Features for Writer Verification
Document examiners use a variety of features to analyze a given handwritten document for writer verification. The challenge in the automatic classification of a pair of documents ...
A. Bhardwaj, A. Singh, Harish Srinivasan, Sargur N...
BMCBI
2008
111views more  BMCBI 2008»
14 years 9 months ago
Comparative optimism in models involving both classical clinical and gene expression information
Background: In cancer research, most clinical variables have already been investigated and are now well established. The use of transcriptomic variables has raised two problems: r...
Caroline Truntzer, Delphine Maucort-Boulch, Pascal...
ESANN
2006
14 years 11 months ago
Lag selection for regression models using high-dimensional mutual information
Mutual information may be used to select the embedding lag of a time series. However, this lag selection is usually limited to the analysis of the mutual information between a pair...
Geoffroy Simon, Michel Verleysen
IJCNN
2008
IEEE
15 years 4 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...