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JIPS
2006
72views more  JIPS 2006»
13 years 4 months ago
A Feature Selection Technique based on Distributional Differences
: This paper presents a feature selection technique based on distributional differences for efficient machine learning. Initial training data consists of data including many featur...
Sung-Dong Kim
TCBB
2010
176views more  TCBB 2010»
13 years 3 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
GRC
2010
IEEE
13 years 2 months ago
A Comparative Study of Threshold-Based Feature Selection Techniques
Given high-dimensional software measurement data, researchers and practitioners often use feature (metric) selection techniques to improve the performance of software quality clas...
Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hu...
MCS
2007
Springer
13 years 10 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
SPLC
2008
13 years 6 months ago
Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
Software Product-lines (SPLs) use modular software components that can be reconfigured into different variants for different requirements sets. Feature modeling is a common method...
Jules White, B. Doughtery, Douglas C. Schmidt