{"title":"具有多聚类的聚类加权建模","authors":"L. Feldkamp, D. Prokhorov, T. Feldkamp","doi":"10.1109/IJCNN.2001.938419","DOIUrl":null,"url":null,"abstract":"Cluster-weighted modeling (CWM) was proposed by Gershenfeld (1999) for density estimation in joint input-output space. In the base CWM algorithm there is a single output cluster for each input cluster. We extend the base CWM to the structure in which multiple output clusters are associated with the same input cluster. We call this CWM with multiclusters and illustrate it with an example.","PeriodicalId":346955,"journal":{"name":"IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Cluster-weighted modeling with multiclusters\",\"authors\":\"L. Feldkamp, D. Prokhorov, T. Feldkamp\",\"doi\":\"10.1109/IJCNN.2001.938419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cluster-weighted modeling (CWM) was proposed by Gershenfeld (1999) for density estimation in joint input-output space. In the base CWM algorithm there is a single output cluster for each input cluster. We extend the base CWM to the structure in which multiple output clusters are associated with the same input cluster. We call this CWM with multiclusters and illustrate it with an example.\",\"PeriodicalId\":346955,\"journal\":{\"name\":\"IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.2001.938419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2001.938419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cluster-weighted modeling (CWM) was proposed by Gershenfeld (1999) for density estimation in joint input-output space. In the base CWM algorithm there is a single output cluster for each input cluster. We extend the base CWM to the structure in which multiple output clusters are associated with the same input cluster. We call this CWM with multiclusters and illustrate it with an example.