Ps22Pdf 关键词 : 数据挖掘 ; 离群检测 ; 异常 ; 高维离群 [gap=695]Key words: Data Mining; Outliers Detection; Exception; High-Dimension Outliers
基于18个网页-相关网页
spatial outliers detection 空间例外检测
distance-based outliers detection 基于距离的孤立点检测
Detection of Grade Outliers 异常成绩检测
In this thesis, the author presents the theory of data mining, and deeply analyzes the algorithms of clustering and outliers detection.
本文介绍了数据挖掘理论,对聚类及孤立点检测算法进行了深入地分析研究。
参考来源 - 基于距离的聚类和孤立点检测算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
In this thesis, the author presents the theory of data mining, and deeply analyzes the algorithms of clustering and outliers detection.
本文介绍了数据挖掘理论，对聚类及孤立点检测算法进行了深入地分析研究。
Deviation detection is a highly interactive task, and outliers must usually be checked manually to see whether they indicate fraud, errors in the data, or some interesting opportunity.
偏差检测是高度交互性的任务，通常需要手动检查离群值，以查明是否存在欺诈倾向、数据错误或者潜在的机遇。
In the following, learn how InfoSphere Warehouse detects outliers and how you can apply deviation detection to your data.
接下来将了解InfoSphere Warehouse如何检测离群值，以及如何对数据应用偏差检测。
应用推荐