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KMeansJava
- 利用Java实现的K-均值算法，K-Mean 分群法是一种分割式分群方法，其主要目标是要在大量高纬的资料点中找出 具有代表性的资料点；这些资料点可以称为群中心，代表点；然后再根据这些群中心，进行后续的处理，可用于数据挖掘中的聚类分析-Java implementation using K-means algorithm, K-Mean grouping method is a fragmented grouping method, whose main goal is to a large nu
lingpipe-3.6.0
- 一个自然语言处理的Java开源工具包。LingPipe目前已有很丰富的功能，包括主题分类（Top Classification）、命名实体识别（Named Entity Recognition）、词性标注（Part-of Speech Tagging）、句题检测（Sentence Detection）、查询拼写检查（Query Spell Checking）、兴趣短语检测（Interseting Phrase Detection）、聚类（Clustering）、字符语言建模（Character
ClusterAnalysis
- Data Mining of JSP example to do the cluster analysis.
Cluster_Analysis
- 用Java语言实现的空间聚类分析程序，对离散点按照距离标准进行分类。-Java language with the spatial clustering analysis procedures, in accordance with the distance between discrete points of criteria.
RandomizableClusterer.java.tar
- 该算法是对weka算法包功能的拓展，是聚类算法中的随机聚类分析。需要weka算法包支持。-The algorithm is a function of the weka package expansion algorithm is stochastic clustering algorithm in cluster analysis. Package to support the needs of weka algorithm.
java
- 聚类分析java设计思想 用于快速聚类分析算法的需求-Cluster analysis java design ideas for fast clustering algorithm needs
ClusteirngAnalysis
- This work presents an implementation of a parallel Fuzzy c-means cluster analysis tool, which implements both aspects of cluster investigation: the calculation of clusters’ centers with the degrees of membership of records to clusters, and
mhjl
- 在科学技术、经济管理中常常要按一定的标准（相似程度或亲疏关系）进行分类。例如，根据生物的某些性状可对生物分类，根据土壤的性质可对土壤分类等。对所研究的事物按一定标准进行分类的数学方法称为聚类分析，它是多元统计“物以类聚”的一种分类方法。由于科学技术、经济管理中的分类界限往往不分明，因此采用模糊聚类方法通常比较符合实际。-In science and technology, economic management, often according to certain criteria (sim
1
- 聚类分析（K-Means)程序实现及展现(-Cluster analysis (K-Means) to achieve and demonstrate procedures (
cluster
- k means cluster for clustering analysis and code implementation
kmeans
- k-means clustering is a method of vector quantization, originally signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the clu
F_JIDtjl
- 模糊聚类分析动态聚类图，R模糊相似矩阵求传递闭包-Fuzzy cluster analysis of dynamic clustering diagram, R fuzzy similar matrix transitive closure of
fei_ss00
- Including AHP, factor analysis, regression analysis, cluster analysis, For lack of EMD, SNR largest independent component analysis algorithm.