这样一来研究者们就可以使用所谓的聚类分析。
第一章介绍聚类分析的基本知识。
Chapter one introduces the basic knowledge of cluster analysis.
阐述了聚类分析的原理和方法。
The method and principle of clustering analysis are expounded.
聚类分析是多元分析的一个分支。
聚类分析是无需指导学习的重要方法。
Clustering analysis is an important method of study without instructions.
基于卫星云图的聚类分析。
本文提出一种新的DEA聚类分析方法。
使用聚类分析等技巧建立人口统计、行为和心理位置图。
Various demographic, behavioural, and psychographic patterns are built up using techniques such as cluster analysis.
而聚类分析是数据挖掘中很重要的分析手段。
Clustering Analysis is one of the most important technologies in data mining.
在聚类分析中应用的有关模糊集理论理论基础。
The theory foundation about fuzzy set theory in cluster analysis application.
通过聚类分析，可以更清楚地认识事物的本质特征。
The essential characters of things can be clearly recognized by clustering analysis.
通过聚类分析，发现舌、脉、主症聚类有明显规律。
Obvious disciplinarian was found of tongue, pulse and main symptoms through cluster analysis.
通过聚类分析，可以更清楚的认识事物的本质特征。
We can know the essential characters of things more clearly by clustering analyse.
对应聚类分析吸取了对应分析和聚类分析的主要优点。
Correspondence cluster analysis abstracts the main advantages existing in correspondence analysis and cluster analysis.
实际应用证明，系统化聚类分析是一种较好的聚类方法。
The practical application shows that the systematic clustering analysis is an effective method.
文中介绍了聚类分析中的聚合法及其在动物分类中的应用。
The agglomerative methods of Cluster Analysis and their application in classifying animals are described.
目前的各种聚类分析方法中，动态聚类法是最为普遍的一种。
Up to now, dynamic clustering method is the most prevalent one in all sorts of clustering analysis methods.
利用因子分析方法形成综合因子，将综合因子进行聚类分析。
The integrated factors come into being by adopting the way of the analysis of the factors through which the cluster analysis are taken to use.
从技术角度看，这个划分过程通常通过预测分析和聚类分析的组合来完成。
From a technical perspective, the segmentation process is commonly performed using a combination of predictive analytics and cluster analysis.
聚类分析是数据挖掘和探索性数据分析中一个极为重要的技术。
Cluster analysis is one of important techniques in data mining and exploratory data analysis.
聚类分析作为数据挖掘的一类功能，是本论文研究的主要内容。
Cluster analysis, as a module and function of data mining, is the main content of this paper.
通过实例验证，表明该新算法能够有效地解决数据聚类分析问题。
The result of the example shows that the new algorithm can efficiently solve data clustering analysis problems.
通过聚类分析，建立了对枳壳药材质量进行计算机辨识的新方法。
By cluster analysis, the method for quality evaluation of Fructus Aurantii was established.
该算法采用期望最大化(EM)聚类分析方法来识别分类及其顺序。
The algorithm USES the Expectation Maximization (EM) clustering method to identify clusters and their sequences.
聚类有效性评价对聚类分析具有重要意义，是聚类分析的瓶颈之一。
The evaluation of clustering validity is important for clustering analysis, and is one of the bottlenecks of clustering analysis.
实验表明，基于镜头的场景边界检测性能优于基于多特征的镜头聚类分析。
Our experimental results demonstrate the performance of scene change detection based on shot is better than that of shot clustering based on multi-features.
本文针对数据聚类分析和最优化问题的相似点，用模拟退火算法进行聚类分析。
In view of the similarities between data clustering analysis and optimization questions, this paper deals with data clustering analysis by using simulation anneal algorithms.
通过综合评判得到评价集的稳定因素，进而用聚类分析方法分离出这些稳定点。
The steady factor of evaluation set is obtained by the method of Fuzzy Cluster Analysis, then the steady points are separated by the method of Fuzzy Cluster Aalysis.
目的应用流行病学和变量聚类分析的数理统计方法，对脑动脉硬化进行中医分型。
Objective To analyses the traditional Chinese medicine syndrome of cerebral arteriosclerosis, by the ways of clinical epidemiology and variable cluster analysis.
目的应用流行病学和变量聚类分析的数理统计方法，对脑动脉硬化进行中医分型。
Objective To analyses the traditional Chinese medicine syndrome of cerebral arteriosclerosis, by the ways of clinical epidemiology and variable cluster analysis.
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