A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization
Text classification (TC) is widely used for organizing digital documents. The issues in TC are numerous characteristics and high-element dimensions. Many pattern classification issues require feature selection (FS), which is pertinent. FS removes unneeded and redundant data from the dataset. The A...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2022
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/278953/1/Wardoyo_PA.pdf |
| _version_ | 1826050352869277696 |
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| author | Widians, Joan Angelina Wardoyo, Retantyo Hartati, Sri |
| author_facet | Widians, Joan Angelina Wardoyo, Retantyo Hartati, Sri |
| author_sort | Widians, Joan Angelina |
| collection | UGM |
| description | Text classification (TC) is widely used for organizing digital documents. The issues in TC are numerous
characteristics and high-element dimensions. Many pattern
classification issues require feature selection (FS), which is pertinent. FS removes unneeded and redundant data from the dataset. The Ant Colony Optimization (ACO) and Grey Wolf
Optimizer (GWO) for FS are the main topics of our thorough
assessment of the literature on the Swarm Intelligence (SI)
algorithm. Furthermore, it illustrates how the hybrid SI
technique is used in FS across various sectors. The hybrid SI technique uses applicable data from various FS methods to find feature subsets with smaller sizes and better classification performance than those found by regular FS algorithms. |
| first_indexed | 2024-03-14T00:02:37Z |
| format | Conference or Workshop Item |
| id | oai:generic.eprints.org:278953 |
| institution | Universiti Gadjah Mada |
| language | English |
| last_indexed | 2024-03-14T00:02:37Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | oai:generic.eprints.org:2789532023-11-01T04:22:52Z https://repository.ugm.ac.id/278953/ A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization Widians, Joan Angelina Wardoyo, Retantyo Hartati, Sri Information and Computing Sciences Text classification (TC) is widely used for organizing digital documents. The issues in TC are numerous characteristics and high-element dimensions. Many pattern classification issues require feature selection (FS), which is pertinent. FS removes unneeded and redundant data from the dataset. The Ant Colony Optimization (ACO) and Grey Wolf Optimizer (GWO) for FS are the main topics of our thorough assessment of the literature on the Swarm Intelligence (SI) algorithm. Furthermore, it illustrates how the hybrid SI technique is used in FS across various sectors. The hybrid SI technique uses applicable data from various FS methods to find feature subsets with smaller sizes and better classification performance than those found by regular FS algorithms. 2022 Conference or Workshop Item PeerReviewed application/pdf en https://repository.ugm.ac.id/278953/1/Wardoyo_PA.pdf Widians, Joan Angelina and Wardoyo, Retantyo and Hartati, Sri (2022) A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization. In: 2022 Seventh International Conference on Informatics and Computing (ICIC), 8-9 December 2022, Denpasar, Bali Indonesia. https://ieeexplore.ieee.org/document/10007019 |
| spellingShingle | Information and Computing Sciences Widians, Joan Angelina Wardoyo, Retantyo Hartati, Sri A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization |
| title | A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization |
| title_full | A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization |
| title_fullStr | A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization |
| title_full_unstemmed | A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization |
| title_short | A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization |
| title_sort | study on text feature selection using ant colony and grey wolf optimization |
| topic | Information and Computing Sciences |
| url | https://repository.ugm.ac.id/278953/1/Wardoyo_PA.pdf |
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