Modified Floating Search Feature Selection Based on Genetic Algorithm
Classification performance is adversely impacted by noisy data .Selecting features relevant to the problem is thus a critical step in classification and difficult to achieve accurate solution, especially when applied to a large data set. In this article, we propose a novel filter-based floating sear...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Subjects: | |
| Online Access: | https://doi.org/10.1051/matecconf/201816401023 |
| _version_ | 1818368618243555328 |
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| author | Homsapaya Kanyanut Sornil Ohm |
| author_facet | Homsapaya Kanyanut Sornil Ohm |
| author_sort | Homsapaya Kanyanut |
| collection | DOAJ |
| description | Classification performance is adversely impacted by noisy data .Selecting features relevant to the problem is thus a critical step in classification and difficult to achieve accurate solution, especially when applied to a large data set. In this article, we propose a novel filter-based floating search technique for feature selection to select an optimal set of features for classification purposes. A genetic algorithm is utilized to increase the quality of features selected at each iteration. A criterion function is applied to choose relevant and high-quality features which can improve classification accuracy. The method is evaluated using 20 standard machine learning datasets of various sizes and complexities. Experimental results with the datasets show that the proposed method is effective and performs well in comparison with previously reported techniques. |
| first_indexed | 2024-12-13T23:10:48Z |
| format | Article |
| id | doaj.art-bea043586b7a4de3b2b43ae78580c3a8 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-13T23:10:48Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-bea043586b7a4de3b2b43ae78580c3a82022-12-21T23:28:07ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011640102310.1051/matecconf/201816401023matecconf_icesti2018_01023Modified Floating Search Feature Selection Based on Genetic AlgorithmHomsapaya KanyanutSornil OhmClassification performance is adversely impacted by noisy data .Selecting features relevant to the problem is thus a critical step in classification and difficult to achieve accurate solution, especially when applied to a large data set. In this article, we propose a novel filter-based floating search technique for feature selection to select an optimal set of features for classification purposes. A genetic algorithm is utilized to increase the quality of features selected at each iteration. A criterion function is applied to choose relevant and high-quality features which can improve classification accuracy. The method is evaluated using 20 standard machine learning datasets of various sizes and complexities. Experimental results with the datasets show that the proposed method is effective and performs well in comparison with previously reported techniques.https://doi.org/10.1051/matecconf/201816401023Feature selectionFloating searchGenetic algorithm |
| spellingShingle | Homsapaya Kanyanut Sornil Ohm Modified Floating Search Feature Selection Based on Genetic Algorithm MATEC Web of Conferences Feature selection Floating search Genetic algorithm |
| title | Modified Floating Search Feature Selection Based on Genetic Algorithm |
| title_full | Modified Floating Search Feature Selection Based on Genetic Algorithm |
| title_fullStr | Modified Floating Search Feature Selection Based on Genetic Algorithm |
| title_full_unstemmed | Modified Floating Search Feature Selection Based on Genetic Algorithm |
| title_short | Modified Floating Search Feature Selection Based on Genetic Algorithm |
| title_sort | modified floating search feature selection based on genetic algorithm |
| topic | Feature selection Floating search Genetic algorithm |
| url | https://doi.org/10.1051/matecconf/201816401023 |
| work_keys_str_mv | AT homsapayakanyanut modifiedfloatingsearchfeatureselectionbasedongeneticalgorithm AT sornilohm modifiedfloatingsearchfeatureselectionbasedongeneticalgorithm |