You'll see that it is like a combination of classification and clustering, and provides another useful weapon for our mission to destroy data misinformation.
您将看到它更像是分类与群集的组合，并为我们消灭数据误导的使命提供了另一种有用的武器。
Data mining commonly involves a few standard tasks that include clustering, classification, regression, and associated rule learning.
数据挖掘通常涉及到一些标准的任务，包括聚集、分类、回归分析和关联性规则学习。
This article discussed two data mining algorithms: the classification tree and clustering.
本文讨论了两种数据挖掘算法：分类树和群集。
Future articles will touch upon other methods of mining data, including clustering, Nearest Neighbor, and classification trees.
本系列后续的文章将会涉及挖掘数据的其他方法，包括群集、最近的邻居以及分类树。
A clustering-based and supervised intrusion detection method was proposed with new distance definition for mixed-attribute data and improved nearest neighbor classification method.
基于一种用于混合属性数据的距离定义和改进的最近邻分类方法，提出了一种基于聚类的有指导的入侵检测方法。
Data Mining mainly studies on research Generalization Knowledge, Association Knowledge, Classification Knowledge, Clustering Knowledge, Prediction Knowledge, and Deviation Knowledge.
数据挖掘主要研究内容包括广义知识、关联知识、分类知识、聚类知识、预测型知识和偏差型知识的内容。
Cluster retrieval method can produce classification of similar data through clustering, and data searching is processed based on this. It can effectively enhance the data retrieval efficiency.
聚类检索通过聚类产生相似数据的分类，并以此为基础进行数据查询，从而提高数据检索的效率。
Data mining always faces complicated tasks that including classification, prediction, association rule discovering and clustering, etc.
数据挖掘面对的任务是复杂的，通常包括分类、预测、关联规则发现和聚类分析等。
Classification and clustering are both commonly used data mining methods. The advantage of classification is that the accuracy is higher, but the labeled training set is needed.
分类和聚类都是常用的数据挖掘方法，分类的优点是准确率较高，但需要带有类别标注的训练集；
This paper found the "good" dataset by using fuzzy clustering and fuzzy neuro-cluster data classification system, which can be used in the candidate selection.
本文研究了模糊聚类方法结合模糊神经分类系统，筛选出了好的数据记录，在优选压裂井时使用。
Clustering analysis is one of the basic methods of the data mining and knowledge finding and it is a non - surveillance data classification method.
聚类分析是在无先验知识无指导下进行数据无监督分类的一种数据挖掘技术。
Using the concept of classification of clustering, the behavior data were classified by probability and frequency, and the model was built for intelligence information analysis.
利用概念分类的聚类思想，使用概率和频率度量对行为数据分类，获得指导情报分析的模型。
Several major kinds of data mining methods, including characterization, classification, association rule, clustering, outlier detection, pattern matching, data visualization, and so on.
常用的数据挖掘方法包括描述、分类、关联规则、聚类、孤立点检测、模式匹配、数据可视化等。
This case USES combined with fuzzy clustering and generalized regression neural network clustering algorithm for intrusion data classification.
本案例采用结合模糊聚类和广义神经网络回归的聚类算法对入侵数据进行分类。
Because traditional clustering methods exist in a number of problems, This paper presents a classification method based on the continuity of data under the class definition and constraints.
针对已有聚类方法中存在的种种问题，本文根据类的定义和约束条件提出了基于数据连续性原理的聚类方法。
Because traditional clustering methods exist in a number of problems, This paper presents a classification method based on the continuity of data under the class definition and constraints.
针对已有聚类方法中存在的种种问题，本文根据类的定义和约束条件提出了基于数据连续性原理的聚类方法。
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