In the final chapter, we mine stock trading data using time series method, find out the model and outliers in the data and, at last, we show the more exact forecasting model and outlier mining method.
第五章利用时间序列的方法对证券交易数据进行了挖掘，找出了数据中的模式和异常，相对传统方法而言，给出了更精确的预测模型和异常挖掘方法。
Outlier data mining is an important embranchment in data mining research.
离群数据挖掘是数据挖掘研究的一个重要分支。
Outlier detection is a very important technique in data mining.
离群点发现是数据挖掘的一项重要技术。
Research on clustering analysis and outlier detection algorithms has become a highly active topic in the data mining research.
聚类及孤立点检测算法研究已经成为数据挖掘研究领域中非常活跃的一个研究课题。
Analysis of outlier mining is one of the important problems in data mining.
孤立点分析是数据挖掘中的一个重要课题。
This paper presents an algorithm for outlier detection in distributed data streams.
针对分布式数据流环境，提出基于核密度估计的分布数据流离群点检测算法。
The detection of outlier is very important in chemistry and chemical engineering which emphasizes experimentation and data acquisition.
局外点检测对于注重试验和数据采集的化学化工领域，其重要性不可忽视。
Data Snooping or outlier detection is a main research subject in measurement data processing and measurement quality controlling.
粗差探测是测量数据处理、测量质量控制的重要研究主题之一。
The recognition of massive outlier data is a problem with a large number of operations in data processing.
批量异常数据的识别是数据处理中的大计算量问题。
Abstract: spatial outlier detection is a research hotspot in the domain of spatial data mining.
摘要：空间离群模式探测是空间数据挖掘的一个研究热点。
To efficiently resolve outlier detection problem in large scale data sets, an efficient outlier detection algorithm based on Support Vector Data Description (SVDD) was proposed.
为了解决大规模数据中的异常检测问题，提出了基于支持向量数据描述（SVDD）的高效离群数据检测算法。
To efficiently resolve outlier detection problem in large scale data sets, an efficient outlier detection algorithm based on Support Vector Data Description (SVDD) was proposed.
为了解决大规模数据中的异常检测问题，提出了基于支持向量数据描述（SVDD）的高效离群数据检测算法。
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