{"title":"随机自组织映射变体与R包SOMbrero","authors":"N. Villa-Vialaneix","doi":"10.1109/WSOM.2017.8020014","DOIUrl":null,"url":null,"abstract":"Self-Organizing Maps (SOM) [ ] are a popular clustering and visualization algorithm. Several implementations of the SOM algorithm exist in different mathematical/statistical softwares, the main one being probably the SOM Toolbox [2]. In this presentation, we will introduce an R package, SOMbrero, which implements several variants of the stochastic SOM algorithm. The package includes several diagnosis tools and graphics for interpretation of the results and is provided with a complete documentation and examples.","PeriodicalId":130086,"journal":{"name":"2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Stochastic self-organizing map variants with the R package SOMbrero\",\"authors\":\"N. Villa-Vialaneix\",\"doi\":\"10.1109/WSOM.2017.8020014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Self-Organizing Maps (SOM) [ ] are a popular clustering and visualization algorithm. Several implementations of the SOM algorithm exist in different mathematical/statistical softwares, the main one being probably the SOM Toolbox [2]. In this presentation, we will introduce an R package, SOMbrero, which implements several variants of the stochastic SOM algorithm. The package includes several diagnosis tools and graphics for interpretation of the results and is provided with a complete documentation and examples.\",\"PeriodicalId\":130086,\"journal\":{\"name\":\"2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSOM.2017.8020014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSOM.2017.8020014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stochastic self-organizing map variants with the R package SOMbrero
Self-Organizing Maps (SOM) [ ] are a popular clustering and visualization algorithm. Several implementations of the SOM algorithm exist in different mathematical/statistical softwares, the main one being probably the SOM Toolbox [2]. In this presentation, we will introduce an R package, SOMbrero, which implements several variants of the stochastic SOM algorithm. The package includes several diagnosis tools and graphics for interpretation of the results and is provided with a complete documentation and examples.
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