Fast Branch & Bound Algorithm in Feature Selection
نویسندگان
چکیده
We introduce a novel algorithm for optimal subset selection. Due to its simple mechanism for predicting criterion values the algorithm finds optimum usually several times faster than any other known Branch & Bound [5], [7] algorithm. This behavior is expected when the algorithm is used in conjunction with non-recursive and/or computationally expensive criterion functions.
منابع مشابه
Branch & Bound Algorithm with Partial Prediction for Use with Recursive and Non-recursive Criterion Forms
We introduce a novel algorithm for optimal feature selection As op posed to our recent Fast Branch Bound FBB algorithm the new algorithm is well suitable for use with recursive criterion forms Even if the new algorithm does not operate as e ectively as the FBB algorithm it is able to nd the optimum signi cantly faster than any other Branch Bound algorithm
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