{"title":"基于空间划分方法的鲁棒模型","authors":"Liming Zhang, WeiPing Fan","doi":"10.1109/ICONIP.1999.844671","DOIUrl":null,"url":null,"abstract":"A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of experiments show that the SP-MLP is more robust than other models. The issue of generalization is also discussed in this paper.","PeriodicalId":237855,"journal":{"name":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A robust model based on space-partitioning method\",\"authors\":\"Liming Zhang, WeiPing Fan\",\"doi\":\"10.1109/ICONIP.1999.844671\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of experiments show that the SP-MLP is more robust than other models. The issue of generalization is also discussed in this paper.\",\"PeriodicalId\":237855,\"journal\":{\"name\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONIP.1999.844671\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONIP.1999.844671","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new model, called the space-partitioning multilayer perceptron (SP-MLP), is proposed in this paper to resolve classification problems. The number of first-hidden-layer units is determined adaptively, and we introduce a new sub-algorithm to improve the robustness of the network. The results of experiments show that the SP-MLP is more robust than other models. The issue of generalization is also discussed in this paper.
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