Feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Stylometry and DNA microarray...

in 1992 that takes a filter-method approach to feature selection that is notably sensitive to feature interactions. It was originally designed for application...

an intermediate step to facilitate other analyses. Feature selection approaches try to find a subset of the input variables (also called features or attributes)...

applications. IEEE Intelligent Systems, Special issue on Feature Transformation and Subset Selection, pp. 30-37, March/April, 1998 Breiman, L. Friedman, T...

various classifier accuracy estimators, feature subset size optimization, feature selection with pre-specified feature weights, criteria ensembles, hybrid...

Patrenahalli M.; Fukunaga, K. (1977). "A branch and bound algorithm for feature subset selection" (PDF). IEEE Transactions on Computers. C-26 (9): 917–922. doi:10...

Intelligence in 2005. Feature selection, one of the basic problems in pattern recognition and machine learning, identifies subsets of data that are relevant...

gradient optimization methods. A natural approximation for the best subset selection problem is the ℓ 1 {\displaystyle \ell _{1}} norm regularization: min...

PMID 25948244. Degroeve S, De Baets B, Van de Peer Y, Rouzé P (2002). "Feature subset selection for splice site prediction". Bioinformatics. 18 (Suppl 2): S75-83...

life-history paradigm has replaced the r / K selection paradigm, but continues to incorporate its important themes as a subset of life history theory. Some scientists...