The paper systematically compares two feature extraction algorithms to mine product features commented on in customer reviews. The first approach [17] identifies candidate featu...
Feature selection is used to improve performance of learning algorithms by finding a minimal subset of relevant features. Since the process of feature selection is computationally ...
Mark Last, Abraham Kandel, Oded Maimon, Eugene Ebe...
Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...