Wrappers for Feature Subset Selection

by: Ron Kohavi, George H John

Artificial Intelligence, Vol. 97, No. 1-2. (1997), pp. 273-324.

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Abstract

In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set, a feature subset selection method should consider how the algorithm and the training set interact. We explore the relation between optimal feature subset selection and relevance. Our wrapper method...

@article{citeulike:1146004, abstract = {In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set, a feature subset selection method should consider how the algorithm and the training set interact. We explore the relation between optimal feature subset selection and relevance. Our wrapper method...}, author = {Kohavi, Ron and John, George H. }, citeulike-article-id = {1146004}, journal = {Artificial Intelligence}, keywords = {feature-selection, learning}, number = {1-2}, pages = {273--324}, posted-at = {2008-03-22 11:39:21}, priority = {4}, title = {Wrappers for Feature Subset Selection}, url = {http://citeseer.ist.psu.edu/13663.html}, volume = {97}, year = {1997} }

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TY - JOUR ID - citeulike:1146004 L3 - citeulike-article-id:1146004 TI - Wrappers for Feature Subset Selection JF - Artificial Intelligence VL - 97 IS - 1-2 SP - 273 EP - 324 N2 - In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set, a feature subset selection method should consider how the algorithm and the training set interact. We explore the relation between optimal feature subset selection and relevance. Our wrapper method... KW - feature-selection KW - learning AU - Kohavi, Ron AU - John, George PY - 1997/// UR - http://citeseer.ist.psu.edu/13663.html ER -

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