Feature selection using tabu search method
نویسندگان
چکیده
Selecting an optimal subset from original large feature set in the design of pattern classi"er is an important and di$cult problem. In this paper, we use tabu search to solve this feature selection problem and compare it with classic algorithms, such as sequential methods, branch and boundmethod, etc., and most other suboptimal methods proposed recently, such as genetic algorithm and sequential forward (backward) #oating search methods. Based on the results of experiments, tabu search is shown to be a promising tool for feature selection in respect of the quality of obtained feature subset and computation e$ciency. The e!ects of parameters in tabu search are also analyzed by experiments. 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
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ورودعنوان ژورنال:
- Pattern Recognition
دوره 35 شماره
صفحات -
تاریخ انتشار 2002