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文章基本信息

  • 标题:Fuzzy based clustering of High Dimensional Datasets
  • 本地全文:下载
  • 作者:M.Pavani ; M.Pravallika ; M. SaiChandan
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2015
  • 卷号:6
  • 期号:2
  • 页码:1518-1520
  • 出版社:TechScience Publications
  • 摘要:Now-A-Days Fuzzy Association Rule Mining (ARM) on high dimensional data is a high topic in many fields of data mining. There are various data repositories such as relational database, transactional data base etc., which stores the data in different dimensions. Applying the association rules on high dimensional data is challenging issue. The main strength of fuzzy ARM is completeness but the strength is overcome by the major drawback i.e., to handle the large number of datasets. Fuzzy ARM is traditional process it is not much efficient. So, FAR-HD process the Fuzzy frequent item sets in a DFS manner. In our paper we are particularly concentrated on problems of Fuzzy ARM on high dimensional data and classification of the high dimensional data.
  • 关键词:Fuzzy Association Rule in High Dimensional data;sets (FAR-HD); SURF (Speed up Robust Feature) Algorithm;Fuzzy C-mean; Fuzzy Association Classification (FAC).
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