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。
A method of detection of outliers from the exponential distribution is given by sample fractile to construct test statistics.
利用样本分位数构造检验统计量，给出来自于指数分布总体异常数据的一种检测方法。
The paper focuses on the sensitivity of local tangent space alignment (LTSA) to outliers, and presents a robust local tangent space alignment (RLTSA) based on outlier detection.
研究局部切空间排列方法(LTSA)对离群点的敏感性，提出一种基于离群点检测的鲁棒局部切空间排列方法(RLTSA)。
The detection of multiple outliers in random effects models of the unbalanced one-way classifications is studied in this paper.
研究了非平衡单向分类随机效应模型中多个异常值的检验问题。
Experimental results show that the presented algorithm is effective in detecting outliers in the outlier subsequences detection and can improve the effectiveness of the outlier subsequences detection.
实验结果表明，所提出的算法对异常子序列的异常检测具有很好的效果，能够有效地提高时间序列中异常子序列检测的效率。
The research of detection of outliers in the linear regression model has been a hot topic all the time for the complexity of the real data.
由于实际数据的复杂性，使得识别回归模型异常点的研究工作一直是个热点。
The research of detection of outliers in the linear regression model has been a hot topic all the time for the complexity of the real data.
由于实际数据的复杂性，使得识别回归模型异常点的研究工作一直是个热点。
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