{"title":"基于场合的模糊谱划分集成","authors":"Xiaolong Meng, Yan Yang, Hongjun Wang","doi":"10.1109/ISKE.2015.47","DOIUrl":null,"url":null,"abstract":"Clustering ensemble takes advantage of ensemble learning technique, combining multiple cluster members' results to get uniform and more reasonable clustering result. This paper integrates in the staged results of spectral partition ensemble algorithm orderly, applying the fuzzy C-means clustering algorithm in the following clustering stage of spectral partition ensemble, and presents four fuzzy spectral partition ensemble based on occasion. Compared with the existing graph partition ensemble algorithms, our algorithms do better in the clustering effectiveness and efficiency.","PeriodicalId":312629,"journal":{"name":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fuzzy Spectral Partition Ensemble Based on Occasion\",\"authors\":\"Xiaolong Meng, Yan Yang, Hongjun Wang\",\"doi\":\"10.1109/ISKE.2015.47\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Clustering ensemble takes advantage of ensemble learning technique, combining multiple cluster members' results to get uniform and more reasonable clustering result. This paper integrates in the staged results of spectral partition ensemble algorithm orderly, applying the fuzzy C-means clustering algorithm in the following clustering stage of spectral partition ensemble, and presents four fuzzy spectral partition ensemble based on occasion. Compared with the existing graph partition ensemble algorithms, our algorithms do better in the clustering effectiveness and efficiency.\",\"PeriodicalId\":312629,\"journal\":{\"name\":\"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISKE.2015.47\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE.2015.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy Spectral Partition Ensemble Based on Occasion
Clustering ensemble takes advantage of ensemble learning technique, combining multiple cluster members' results to get uniform and more reasonable clustering result. This paper integrates in the staged results of spectral partition ensemble algorithm orderly, applying the fuzzy C-means clustering algorithm in the following clustering stage of spectral partition ensemble, and presents four fuzzy spectral partition ensemble based on occasion. Compared with the existing graph partition ensemble algorithms, our algorithms do better in the clustering effectiveness and efficiency.