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- This article promoted outlier data mining algorithms based on weighted fast clustering to inspect and deal with outlier data effectively. 设计了基于加权快速聚类的异常数据挖掘算法,以便能快速发现异常数据。
- In this paper,authors analyze and evaluate several major methods of the outlier data mining,and propose a new outlier detection algorithm which is based on an genetic algorithm for clustering. 对离群数据挖掘几类主要的方法进行了分析和评价,并在此基础上了提出了一种基于遗传聚类的离群点检测算法。
- Outlier mining is an important part of data mining. 摘要离群数据挖掘是数据挖掘的重要内容。
- Outlier Data Mining and its Applicationin the Authentication for Materiel Consumption of Blast Furnace 离群数据挖掘在高炉物料消耗数据认证中的应用
- outlier data mining 离群数据挖掘
- Data mining is to extract knowledge from information. 资料开采是从各种资讯中获得知识。
- Clustering is a major method of data mining. 摘要聚类是数据挖掘中的主要方法。
- The existing researches on outlier data mainly focus on the outlier detection. 摘要现有离群数据研究主要集中于离群检测。
- Outlier mining has become a hot issue in the field of data mining,which is to find exceptional objects that deviate from the most rest of the data set. 离群点检测作为数据挖掘的一个重要研究方向;可以从大量数据中发现少量与多数数据有明显区别的数据对象.
- Understanding data mining may be important to you. 理解数据挖掘可能对你很重要。
- In its most basic form, data mining is very simple. 以其最基本的方式,数据采集就简单了。
- Data mining tools yield five types of information. 数据开采工具得到五类信息。
- An available answer is Data Mining. 可行的方法之一就是利用数据挖掘技术。
- CUG, Research Areas: Database and Data Mining. 研究生毕业,研究方向:数据库与数据挖掘技术。
- The method can be used to filtrate the outlier data and discover clusters of arbitrary shape. 这种方法可以用来过滤“噪声”孤立点数据,发现任意形状的簇。
- Outlier detection,as an important aspect of data mining,provides a new method for analyzing various quantitative,complex and noisy data. 摘要 离群点检测是数据挖掘一个重要内容,它为分析各种海量的、复杂的、含有噪声的数据提供了新的方法。
- Outlier mining has become a hot issue in the field of data mining, which is to find exceptional objects that deviate from the most rest of the data set. 摘要离群点检测作为数据挖掘的一个重要研究方向,可以从大量数据中发现少量与多数数据有明显区别的数据对象。
- Primary research results show that such data mining methods as clustering, classification, association, time-series analysis and outlier analysis are feasible in the FDD of LRE. 分析表明,聚类、类、联、间序列分析和孤立点检测等数据挖掘方法适用于液体火箭发动机的故障检测和诊断。
- Data mining in data stream, such as clustering, classifying, etc, becomes a hot research field.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。
- In the near future study of the distributed data mining. 文摘链接:分布式数据开采研究。
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