Correlation Analysis of Big Data to Support Machine Learning

被引：8
|
作者：
Pandey, Rajiv [1 ]
Dhoundiyal, Manoj [2 ]
Kumar, Amrendra [2 ]
机构：
[1] Amity Univ, Amity Inst Informat Technol, Lucknow, Uttar Pradesh, India
[2] Amity Univ, IT Dept, Lucknow, Uttar Pradesh, India
来源：
2015 FIFTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT2015) | 2015年
关键词：
Quantitative Variables; R; Correlation analysis; Big Data; Linear Model; Linear Regression;
D O I：
10.1109/CSNT.2015.32
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The large size and complexity of datasets in Big Data need specialized statistical tools for analysis and we use R for correlation analysis of our data set. This paper explores the correlation analysis through best fit linear regression of quantitative variables with help of the demonstration based on scatter plots and linear regression best fit line. The analysis demonstrated in this paper is scalable to Big Data in any other context where the quantitative variables are clearly delineated. R provides multiple techniques and inferences to statistical analysis of dataset, this paper however explores the correlation between quantitative variable establishing the extent of dependability between them using R functions. The correlation and best fit line functions of R i.e. cor() and abline( lmout) respectively are significantly explored.
引用
收藏
页码：996 / 999
页数：4
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