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- W2137074470 abstract "This paper presents a novel generalized steepest ascent algorithm for selecting a subset of features. Our proposed algorithm is an improvement upon the prior steepest ascent algorithm by selecting a better starting search point and performing a more thorough search than the steepest ascent algorithm. For any given criterion function used to evaluate the effectiveness of a selected feature subsets, our method is guaranteed to provide solutions that equal or exceed those of the state-of-the-art sequential forward floating selection algorithm. Experimental results for two real data sets confirm that our algorithm consistently selects better subsets than other well-known suboptimal feature selection algorithms do." @default.
- W2137074470 created "2016-06-24" @default.
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- W2137074470 date "2009-10-01" @default.
- W2137074470 modified "2023-09-25" @default.
- W2137074470 title "Feature subset selection using generalized steepest ascent search algorithm" @default.
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- W2137074470 doi "https://doi.org/10.1109/snlp.2009.5340930" @default.
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