An ensemble based approach for feature selection

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Abstract

This paper proposes an ensemble based approach for feature selection. We aim at overcoming the problem of parameter sensitivity of feature selection approaches. To do this we employ ensemble method. We get the results per different possible threshold values automatically in our algorithm. For each threshold value, we get a subset of features. We give a score to each feature in these subsets. Finally by use of ensemble method, we select the features which have the highest scores. This method is not a parameter sensitive one, and also it has been shown that using the method based on the fuzzy entropy results in more reliable selected features than the previous methods'. Empirical results show that although the efficacy of the method is not considerably decreased in most of cases, the method becomes free from setting of any parameter. © 2011 International Federation for Information Processing.

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Minaei-Bidgoli, B., Asadi, M., & Parvin, H. (2011). An ensemble based approach for feature selection. In IFIP Advances in Information and Communication Technology (Vol. 363 AICT, pp. 240–246). https://doi.org/10.1007/978-3-642-23957-1_27

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