| Learning Causality Diagram Structure Based on Genetic Algorithm |
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| 作者姓名： | SHI Qing-xi~ |
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| 作者单位： | 1. Deptartment of Computer, Chongqing Technology and Business University, Chongqing 400067, China; 2. College of Automation, Chongqing University, Chongqing 400030, China |
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| 摘 要： | The Causality Diagram theory,which adopted graphical expression of knowledge and direct causality intensity of causality,overcomes some shortages in Belief Network and has evolved into a mixed causality diagram methodology coped with discrete and continuous variable.But it is difficult that the structure of Causality Diagram given by expert.Because the complexity of causality diagram structure goes up exponentially through the number of the vertex's increasing,it is NP-hard problem to find the most possible structure from a set of data.The authors discuss approaches and present Genetic Algorithm,to find the most possible structure from a set of data.Experiment shows the method is effective.
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| 关 键 词： | causality diagram causality diagram structure machine learning genetic algorithm |
| 收稿时间： | 2005/12/7 0:00:00 |
| 修稿时间： | 2005/12/7 0:00:00 |
Learning Causality Diagram Structure Based on Genetic Algorithm |
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| SHI Qing-xi.Learning Causality Diagram Structure Based on Genetic Algorithm[J].Storage & Process,2006(4):111-114. |
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| Authors: | SHI Qing-xi |
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| Institution: | 1. Deptartment of Computer, Chongqing Technology and Business University, Chongqing 400067, China; 2. College of Automation, Chongqing University, Chongqing 400030, China |
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| Abstract: | The Causality Diagram theory,which adopted graphical expression of knowledge and direct causality intensity of causality,overcomes some shortages in Belief Network and has evolved into a mixed causality diagram methodology coped with discrete and continuous variable.But it is difficult that the structure of Causality Diagram given by expert.Because the complexity of causality diagram structure goes up exponentially through the number of the vertex's increasing,it is NP-hard problem to find the most possible structure from a set of data.The authors discuss approaches and present Genetic Algorithm,to find the most possible structure from a set of data.Experiment shows the method is effective. |
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| Keywords: | causality diagram causality diagram structure machine learning genetic algorithm |
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