Feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Stylometry and DNA microarray...
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in 1992 that takes a filter-method approach to feature selection that is notably sensitive to feature interactions. It was originally designed for application...
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Dimensionality reduction (section Feature selection)
an intermediate step to facilitate other analyses. Feature selection approaches try to find a subset of the input variables (also called features or attributes)...
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applications. IEEE Intelligent Systems, Special issue on Feature Transformation and Subset Selection, pp. 30-37, March/April, 1998 Breiman, L. Friedman, T...
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various classifier accuracy estimators, feature subset size optimization, feature selection with pre-specified feature weights, criteria ensembles, hybrid...
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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...
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Intelligence in 2005. Feature selection, one of the basic problems in pattern recognition and machine learning, identifies subsets of data that are relevant...
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Structured sparsity regularization (redirect from Best subset selection)
gradient optimization methods. A natural approximation for the best subset selection problem is the ℓ 1 {\displaystyle \ell _{1}} norm regularization: min...
24 KB (3,812 words) - 20:48, 26 October 2023
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...
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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...
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