孤立点分析是数据挖掘中的一个重要课题。
Analysis of outlier mining is one of the important problems in data mining.
基于偏离的孤立点探测方法是孤立点分析一个重要的技术。
The offset-based outlier mining detecting method is a key technique for analysis of outlier mining.
孤立点挖掘又称孤立点分析、异常检测、例外挖掘、小事件检测、挖掘极小类、偏差检测。
The problem of outlier mining has been variously called outlier analysis, anomaly detection, exception mining, detecting rare events, mining rare classes, deviation detection, etc.
在模式挖掘方面,集成了目前有效的最大向前路径挖掘算法和频繁遍历路径挖掘算法,并且将孤立点分析方法引入日志挖掘中。
Efficient mining algorithm of maximum forward path and efficient mining algorithm of frequent traversal path are integrated in the mining period; Outlier analysis is introduced into the mining system.
为此,把孤立点分析算法应用于设备维护案例不一致性的辨识,并对一组实际的风机机组案例库片断进行孤立点分析,找出了不一致案例。
So, a technology of plant maintenance case inconsistency identification on Outlier analysis is provided, and in this way, an inconsistency case is found out from a set of blower fan team's case bases.
目前,在时间序列分析领域,孤立点的挖掘越来越多的受到重视。
At present, outlier mining has attached a great importance in the field of time series analysis.
目前,在时间序列分析领域,孤立点的挖掘越来越多的受到重视。
At present, outlier mining has attached a great importance in the field of time series analysis.
应用推荐