| A spatial entropy reflecting distribution of spatial objects |
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| 作者姓名： | Youn-Kyung Jang Byeong-Seob You Ho-Seok Kim Kyoung-Bae Kim Hae-Young Bae |
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| 作者单位： | Dept. of Computer Science and Information Engineering Inha University，Dept. of Computer Science and Information Engineering Inha University，Dept. of Computer Science and Information Engineering Inha University，Department of Computer Education Seowon University，Dept. of Computer Science and Information Engineering Inha University，Incheon 402-751 Korea，Incheon 402-751 Korea，Incheon 402-751 Korea，Chungbuk 361-742 Korea，Incheon 402-751 Korea |
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| 摘 要： |
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A spatial entropy reflecting distribution of spatial objects |
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| Youn-Kyung Jang,Byeong-Seob You,Ho-Seok Kim,Kyoung-Bae Kim,Hae-Young Bae.A spatial entropy reflecting distribution of spatial objects[J].Journal of Chongqing University of Posts and Telecommunications(Natural Sciences Edition),2007(3). |
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| Authors: | Youn-Kyung Jang Byeong-Seob You Ho-Seok Kim Kyoung-Bae Kim Hae-Young Bae |
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| Institution: | Youn-Kyung Jang1,Byeong-Seob You1,Ho-Seok Kim1,Kyoung-Bae Kim2,Hae-Young Bae1 |
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| Abstract: | Decision trees are mainly used to classify data and predict data classes. A spatial decision tree has been designed using Euclidean distance between objects for reflecting spatial data characteristic. Even though this method explains the distance of objects in spatial dimension, it fails to represent distributions of spatial data and their relationships. But distributions of spatial data and relationships with their neighborhoods are very important in real world. This paper proposes decision tree based on spatial entropy that represents distributions of spatial data with dispersion and dissimilarity. The rate of dispersion by dissimilarity presents how related distribution of spatial data and non-spatial attributes. The experiment evaluates the accuracy and building time of decision tree as compared to previous methods and it shows that the proposed method makes efficient and scalable classification for spatial decision support. |
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| Keywords: | spatial decision tree spatial entropy decision support |
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