Sequential floating search

Danyo83Danyo83 Member Posts: 41 Contributor II
edited June 2019 in Help

pure greedy approaches for feature selection have the disadvantage that once a feature is chosen or eliminated this decision cannot be revoked even if the learner would be better. Therefore one could use floating methods. For example one let choose the best random features (or GA based search) after 100 iterations. After that one combines sequential forward selection and backward elimination in a row and multiple times until there is no further improvement.
Would be a great tool for RM.



  • Options
    wesselwessel Member Posts: 537 Maven
    There is GA based feature selection: "Optimize Selection (Evolutionary)"?

    Also there is entire feature selection extension? And P-Rules extension with different selection operators?

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