A STUDY ON FEATURE SELECTION IN BIG DATA

被引:0
|
作者
Manikandan, R. P. S. [1 ]
Kalpana, A. M. [2 ]
机构
[1] Sri Shakthi Inst Engn & Technol, Dept IT, Coimbatore, Tamil Nadu, India
[2] Govt Coll Engn, Dept CSE, Salem, Tamil Nadu, India
关键词
Big Data; Feature Selection; Clustering Algoruthm; Map reduce techniques;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The scale of big data is increasing in every minute, and it becomes important to handle massive data. The familiar problem of Big data is not only huge volume but also planned in many places to provide high dimensionality in feature selection. In numerous big data application, feature selection is significant to select the essential features from the known data set and it removes unrelated and disused features for the better approach by means of clustering process. Based on the criterion of time efficiency provides difficulty and efficiency as per the data value, essential required feature selection approaches are retrieved from big data. The computational complication of learning and calculating algorithms is reduced by the feature selection and a non-selected feature saves measuring cost. In this study, a review is made on big data.
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页数:5
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