Abstract
A large package of algorithms for feature ranking and selection has been developed. Infosel++, Information Based Feature Selection C++ Library, is a collection of classes and utilities based on probability estimation that can help developers of machine learning methods in rapid interfacing of feature selection algorithms, aid users in selecting an appropriate algorithm for a given task (embed feature selection in machine learning task), and aid researchers in developing new algorithms, especially hybrid algorithms for feature selection. A few examples of such possibilities are presented.
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