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BMCBI
2008
186views more  BMCBI 2008»
13 years 7 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
BMCBI
2005
118views more  BMCBI 2005»
13 years 7 months ago
Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
Background: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be us...
Thanyaluk Jirapech-Umpai, J. Stuart Aitken
IJPRAI
2002
93views more  IJPRAI 2002»
13 years 7 months ago
Improving Stability of Decision Trees
Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...
Mark Last, Oded Maimon, Einat Minkov
ICPR
2008
IEEE
14 years 2 months ago
Weighted solution path algorithm of support vector regression for abnormal data
In the solution path algorithm of support vector regression, the penalty for violation of the required error is considered equally for every training sample, which means every tra...
Wen-tao Mao, Long-lei Dong, Gang Zhang
PROMISE
2010
13 years 2 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies