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» Ensemble-based Feature Selection Criteria
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MCS
2007
Springer
13 years 9 months ago
Stopping Criteria for Ensemble-Based Feature Selection
Selecting the optimal number of features in a classifier ensemble normally requires a validation set or cross-validation techniques. In this paper, feature ranking is combined with...
Terry Windeatt, Matthew Prior
MCS
2007
Springer
13 years 9 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
MCS
2009
Springer
13 years 10 months ago
Ensemble Based Data Fusion for Gene Function Prediction
The availability of an ever increasing amount of data sources due to recent advances in high throughput biotechnologies opens unprecedented opportunities for genome-wide gene funct...
Matteo Re, Giorgio Valentini
JMLR
2012
11 years 6 months ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
MLDM
2007
Springer
13 years 9 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...