A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural Learning
The Bayesian Network (BN) has been widely applied to causal reasoning in artificial intelligence, and the Search-Score (SS) method has become a mainstream approach to mine causal relationships for establishing BN structure. Aiming at the problems of local optimum and low generalization in existing S...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/12/12/2054 |
| _version_ | 1797545016407621632 |
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| author | Ming Li Ren Zhang Kefeng Liu |
| author_facet | Ming Li Ren Zhang Kefeng Liu |
| author_sort | Ming Li |
| collection | DOAJ |
| description | The Bayesian Network (BN) has been widely applied to causal reasoning in artificial intelligence, and the Search-Score (SS) method has become a mainstream approach to mine causal relationships for establishing BN structure. Aiming at the problems of local optimum and low generalization in existing SS algorithms, we introduce the Ensemble Learning (EL) and causal analysis to propose a new BN structural learning algorithm named C-EL. Combined with the Bagging method and causal Information Flow theory, the EL mechanism for BN structural learning is established. Base learners of EL are trained by using various SS algorithms. Then, a new causality-based weighted ensemble way is proposed to achieve the fusion of different BN structures. To verify the validity and feasibility of C-EL, we compare it with six different SS algorithms. The experiment results show that C-EL has high accuracy and a strong generalization ability. More importantly, it is capable of learning more accurate structures under the small training sample condition. |
| first_indexed | 2024-03-10T14:09:43Z |
| format | Article |
| id | doaj.art-66ca2aff8fec4a2f847caee50d49c038 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-10T14:09:43Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-66ca2aff8fec4a2f847caee50d49c0382023-11-21T00:18:07ZengMDPI AGSymmetry2073-89942020-12-011212205410.3390/sym12122054A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural LearningMing Li0Ren Zhang1Kefeng Liu2College of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, ChinaThe Bayesian Network (BN) has been widely applied to causal reasoning in artificial intelligence, and the Search-Score (SS) method has become a mainstream approach to mine causal relationships for establishing BN structure. Aiming at the problems of local optimum and low generalization in existing SS algorithms, we introduce the Ensemble Learning (EL) and causal analysis to propose a new BN structural learning algorithm named C-EL. Combined with the Bagging method and causal Information Flow theory, the EL mechanism for BN structural learning is established. Base learners of EL are trained by using various SS algorithms. Then, a new causality-based weighted ensemble way is proposed to achieve the fusion of different BN structures. To verify the validity and feasibility of C-EL, we compare it with six different SS algorithms. The experiment results show that C-EL has high accuracy and a strong generalization ability. More importantly, it is capable of learning more accurate structures under the small training sample condition.https://www.mdpi.com/2073-8994/12/12/2054Bayesian networkstructural learningensemble learninginformation flow |
| spellingShingle | Ming Li Ren Zhang Kefeng Liu A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural Learning Symmetry Bayesian network structural learning ensemble learning information flow |
| title | A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural Learning |
| title_full | A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural Learning |
| title_fullStr | A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural Learning |
| title_full_unstemmed | A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural Learning |
| title_short | A New Ensemble Learning Algorithm Combined with Causal Analysis for Bayesian Network Structural Learning |
| title_sort | new ensemble learning algorithm combined with causal analysis for bayesian network structural learning |
| topic | Bayesian network structural learning ensemble learning information flow |
| url | https://www.mdpi.com/2073-8994/12/12/2054 |
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