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Furthermore, in the design of the RA-based PSC model of questions classification, several feature selection approaches are investigated.
Furthermore, a hybrid clustering solution selection strategy (HCSS) is designed based on a proposed weighting function, which combines several feature selection techniques for the refinement of clustering solutions in the ensemble.
For each classification model we evaluated several feature selection approaches by using 10-fold-cross-validation.
We tried several feature selection methods to see how they would affect the accuracy of our sentiment analysis.
Evolutionary algorithms, such as genetic algorithms (GAs) [3] and genetic programming (GP) [4], are encountered in several feature selection approaches in the literature (see, e.g., [5, 6]).
Previous studies have explored several feature selection methods in gamma sub-band range for the identification of alcoholics using the same database.
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Empirical results verify that our algorithm is efficient and achieves better accuracy than several representative feature selection algorithms for three typical classifiers on various datasets.
Extensive empirical results demonstrate the advantage of MDFS over several compared feature selection methods.
To further illustrate the effectiveness of CCLS, it is compared to several established feature selection methods.
There are several automated feature selection methods, ranging from backward, forward or stepwise procedures, to further elaborated methodologies such as evolutionary programming.
Finally, in [13], a survey of several other feature selection methods was presented, leading the authors to conclude that "applying first a method of automatic feature construction yields improved performance and a more compact set of features".
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