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Feature selection
Feature selection, also known as subset selection or variable selection, is a process commonly used in machine learning, wherein a subset of the features available from the data are selected for application of a learning algorithm. Feature selection is necessary either because it is computationally infeasible to use all available features, or because of problems of estimation when limited data samples (but a large number of features) are present.
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