[1]苗永春,程艳.离群点检测方法及其在大数据时代下的改进方法研究[J].江西师范大学学报(自然科学版),2014,(05):454-458.
 MIAO Yong-chun,CHENG Yan.The Outlier Detection Method and Its Improvement in the Eea of Big Data[J].,2014,(05):454-458.
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离群点检测方法及其在大数据时代下的改进方法研究()
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《江西师范大学学报》(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2014年05期
页码:
454-458
栏目:
出版日期:
2014-10-31

文章信息/Info

Title:
The Outlier Detection Method and Its Improvement in the Eea of Big Data
作者:
苗永春;程艳
江西师范大学计算机信息工程学院,江西 南昌,330022
Author(s):
MIAO Yong-chun;CHENG Yan
关键词:
大数据离群点检测方法改进策略
Keywords:
big dataoutlier detection methodimprovement strategies
分类号:
TP391;TP311
文献标志码:
A
摘要:
通过对当前有代表性的离群数据检测方法的分析和比较,总结了各方法的特性及优缺点。针对大数据的数据量大、维数高的特性,分析了离群点检测方法的改进策略,并以 T-ODCD 算法和 AROD 算法为例,进一步说明离群点检测改进策略。
Abstract:
The paper compared and analyzed major outlier detection method and their features and merit and demerit were summarized. In addition,in view of the large amount of data and high dimension of the big data,improvement strategies of outlier detection method were analyzed. Improvement strategies of outlier detection were further illustra-ted by T-ODCD and AROD algorithms.

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备注/Memo

备注/Memo:
国家社科基金教育学青年课题“教育虚拟社区的群集智能化构建方法研究”(CCA110109)
更新日期/Last Update: 1900-01-01