A new binary grasshopper optimization algorithm for feature selection problem
The grasshopper optimization algorithm is one of the recently population-based optimization techniques inspired by the behaviours of grasshoppers in nature. It is an efficient optimization algorithm and since demonstrates excellent performance in solving continuous problems, but cannot resolve direc...
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| Format: | Article |
| Language: | English |
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Springer
2022-02-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157819308900 |
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| author | Haouassi Hichem Merah Elkamel Mehdaoui Rafik Maarouk Toufik Mesaaoud Chouhal Ouahiba |
| author_facet | Haouassi Hichem Merah Elkamel Mehdaoui Rafik Maarouk Toufik Mesaaoud Chouhal Ouahiba |
| author_sort | Haouassi Hichem |
| collection | DOAJ |
| description | The grasshopper optimization algorithm is one of the recently population-based optimization techniques inspired by the behaviours of grasshoppers in nature. It is an efficient optimization algorithm and since demonstrates excellent performance in solving continuous problems, but cannot resolve directly binary optimization problems. Many optimization problems have been modelled as binary problems since their decision variables varied in binary space such as feature selection in data classification. The main goal of feature selection is to find a small size subset of feature from a sizeable original set of features that optimize the classification accuracy. In this paper, a new binary variant of the grasshopper optimization algorithm is proposed and used for the feature subset selection problem. This proposed new binary grasshopper optimization algorithm is tested and compared to five well-known swarm-based algorithms used in feature selection problem. All these algorithms are implemented and experimented assessed on twenty data sets with various sizes. The results demonstrated that the proposed approach could outperform the other tested methods. |
| format | Article |
| id | doaj-art-9e299bf5bb5f45d2b0bed1a48f4e9836 |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2022-02-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-9e299bf5bb5f45d2b0bed1a48f4e98362025-08-20T03:51:59ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782022-02-0134231632810.1016/j.jksuci.2019.11.007A new binary grasshopper optimization algorithm for feature selection problemHaouassi Hichem0Merah Elkamel1Mehdaoui Rafik2Maarouk Toufik Mesaaoud3Chouhal Ouahiba4Corresponding author.; Univ Khenchela, Fac. ST, Lab., BP 1252 El Houria, 40004 Khenchela, AlgeriaUniv Khenchela, Fac. ST, Lab., BP 1252 El Houria, 40004 Khenchela, AlgeriaUniv Khenchela, Fac. ST, Lab., BP 1252 El Houria, 40004 Khenchela, AlgeriaUniv Khenchela, Fac. ST, Lab., BP 1252 El Houria, 40004 Khenchela, AlgeriaUniv Khenchela, Fac. ST, Lab., BP 1252 El Houria, 40004 Khenchela, AlgeriaThe grasshopper optimization algorithm is one of the recently population-based optimization techniques inspired by the behaviours of grasshoppers in nature. It is an efficient optimization algorithm and since demonstrates excellent performance in solving continuous problems, but cannot resolve directly binary optimization problems. Many optimization problems have been modelled as binary problems since their decision variables varied in binary space such as feature selection in data classification. The main goal of feature selection is to find a small size subset of feature from a sizeable original set of features that optimize the classification accuracy. In this paper, a new binary variant of the grasshopper optimization algorithm is proposed and used for the feature subset selection problem. This proposed new binary grasshopper optimization algorithm is tested and compared to five well-known swarm-based algorithms used in feature selection problem. All these algorithms are implemented and experimented assessed on twenty data sets with various sizes. The results demonstrated that the proposed approach could outperform the other tested methods.http://www.sciencedirect.com/science/article/pii/S1319157819308900Swarm intelligenceGrasshopper optimizationFeature selection and binary search space |
| spellingShingle | Haouassi Hichem Merah Elkamel Mehdaoui Rafik Maarouk Toufik Mesaaoud Chouhal Ouahiba A new binary grasshopper optimization algorithm for feature selection problem Journal of King Saud University: Computer and Information Sciences Swarm intelligence Grasshopper optimization Feature selection and binary search space |
| title | A new binary grasshopper optimization algorithm for feature selection problem |
| title_full | A new binary grasshopper optimization algorithm for feature selection problem |
| title_fullStr | A new binary grasshopper optimization algorithm for feature selection problem |
| title_full_unstemmed | A new binary grasshopper optimization algorithm for feature selection problem |
| title_short | A new binary grasshopper optimization algorithm for feature selection problem |
| title_sort | new binary grasshopper optimization algorithm for feature selection problem |
| topic | Swarm intelligence Grasshopper optimization Feature selection and binary search space |
| url | http://www.sciencedirect.com/science/article/pii/S1319157819308900 |
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