{"title":"Automatic off-line multivariate data analysis","authors":"G. Sebestyen","doi":"10.1145/1464291.1464365","DOIUrl":null,"url":null,"abstract":"Many research problems in the social and physical sciences require the collection of large amounts of data of the simultaneously measured attributes of a phenomenon or process under investigation. Pattern recognition problems, in particular, yield data of multiple variables for each manifestation of the different sources of data. The automatic off-line multivariate analysis techniques described in this paper deal with the quantitative description of data of this type.","PeriodicalId":297471,"journal":{"name":"AFIPS '66 (Fall)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1899-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AFIPS '66 (Fall)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1464291.1464365","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Many research problems in the social and physical sciences require the collection of large amounts of data of the simultaneously measured attributes of a phenomenon or process under investigation. Pattern recognition problems, in particular, yield data of multiple variables for each manifestation of the different sources of data. The automatic off-line multivariate analysis techniques described in this paper deal with the quantitative description of data of this type.
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