Survey of research on application of heuristic algorithm in machine learning
Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.T...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2019-12-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2019242/ |
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| _version_ | 1841539357655171072 |
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| author | Yanping SHEN Kangfeng ZHENG Chunhua WU Yixian YANG |
| author_facet | Yanping SHEN Kangfeng ZHENG Chunhua WU Yixian YANG |
| author_sort | Yanping SHEN |
| collection | DOAJ |
| description | Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.Then,the advantages of the heuristic algorithm were illustrated from its applications in machine learning,including the parameter and structure optimization of neural network and other machine learning algorithms,feature optimization,ensemble pruning,prototype optimization,weighted voting ensemble and kernel function learning.Finally,the heuristic algorithms and their development directions in the field of machine learning were given according to the actual needs. |
| format | Article |
| id | doaj-art-7b012d26441542bd8717df763c680d73 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2019-12-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-7b012d26441542bd8717df763c680d732025-01-14T07:18:06ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2019-12-014012413759730965Survey of research on application of heuristic algorithm in machine learningYanping SHENKangfeng ZHENGChunhua WUYixian YANGAiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.Then,the advantages of the heuristic algorithm were illustrated from its applications in machine learning,including the parameter and structure optimization of neural network and other machine learning algorithms,feature optimization,ensemble pruning,prototype optimization,weighted voting ensemble and kernel function learning.Finally,the heuristic algorithms and their development directions in the field of machine learning were given according to the actual needs.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2019242/parameter and structure optimizationfeature optimizationensemble pruningprototype optimizationweighted voting ensemblekernel function learning |
| spellingShingle | Yanping SHEN Kangfeng ZHENG Chunhua WU Yixian YANG Survey of research on application of heuristic algorithm in machine learning Tongxin xuebao parameter and structure optimization feature optimization ensemble pruning prototype optimization weighted voting ensemble kernel function learning |
| title | Survey of research on application of heuristic algorithm in machine learning |
| title_full | Survey of research on application of heuristic algorithm in machine learning |
| title_fullStr | Survey of research on application of heuristic algorithm in machine learning |
| title_full_unstemmed | Survey of research on application of heuristic algorithm in machine learning |
| title_short | Survey of research on application of heuristic algorithm in machine learning |
| title_sort | survey of research on application of heuristic algorithm in machine learning |
| topic | parameter and structure optimization feature optimization ensemble pruning prototype optimization weighted voting ensemble kernel function learning |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2019242/ |
| work_keys_str_mv | AT yanpingshen surveyofresearchonapplicationofheuristicalgorithminmachinelearning AT kangfengzheng surveyofresearchonapplicationofheuristicalgorithminmachinelearning AT chunhuawu surveyofresearchonapplicationofheuristicalgorithminmachinelearning AT yixianyang surveyofresearchonapplicationofheuristicalgorithminmachinelearning |