搜索资源列表
JAVA实现文本聚类，用到TF/IDF权重
- JAVA实现文本聚类，用到TF/IDF权重，用余弦夹角计算文本相似度，用k-means进行数据聚类等数学和统计 知识。,JAVA realization of text clustering, using TF/IDF weight, calculated using cosine angle between the text of similarity, using k-means clustering for data such as mathematical and statistical
demo
- 实现数据挖掘的几个算法，包括模糊聚类，K均值，以及K近邻等聚类算法-Some of the implementation of data mining algorithms, including fuzzy clustering, K-means, as well as neighbors, such as clustering algorithm K
K-means_clustering_demo
- K-均值聚类算法 vc++图形演示程序-K-means clustering algorithm c++ demo program
TDIDF_Demo
- 基于k-means的文本聚类程序实现，希望对大家有帮助！-Based on the k-means clustering procedures for the realization of the text, I hope all of you help!
k-meams(sourcecode)
- C#实现k均值文本聚类算法，文本聚类C#源程序，k-means聚类算法-C# to achieve k means clustering algorithm, document clustering C# source code, k-means clustering algorithm
KClustering
- k-聚类算法-k- gathers a kind of algorithm
K
- K均值算法-分类器-有效抑制边缘点影响-简单有效-K-means algorithm- Classifier- effectively inhibiting the impact of edge points- simple and effective
KAV
- KAV是利用Visual C++ 6.0编写的一个小程序，能实现对特定数据结果的文本数据进行聚类分析，所使用的聚类方法是K均值。 -KAV is the use of Visual C++ 6.0 to prepare a small procedure to achieve the outcome of specific data on the text data clustering analysis, the use of the K-means clustering method.
kMeans
- k-mean image clustering source code developed using java
K-Means
- K_Means（java）算法的实现,有界面，灵活性强，交互性强。-K_Means (java) algorithm, there are interfaces, flexibility, and strong interaction.
kmeans
- java k均值源码，实现了k-means的算法，并给出界面显示。实例中通过二维空间中的点进行聚类。-java k-means algorithm, display the cluster result on the two demension.
MyCluster
- 聚类算法中的k均值算法，里面已经包含一个文本聚类的实验。-Clustering algorithm k means algorithm, which already contains a text clustering experiments.
k-means_Program
- k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。 -k-means algorithm to accept input k then n-k of data objects into a cluster in order to make the cluster available to meet: t
TextClusteringKmeans
- 从文本文件读入文本，分词，去停顿词，然后利用kmeans进行文本聚类-Text Clustering with K means
Kmeans
- K-means算法实现文本聚类，Java实现的版本-K-means algorithm for text clustering
e4k-means-althogrim
- 基于K—Means的中文文本聚类算法的研究和实现。中文文本聚类的主要技术，特征选择，共享最近邻的K-Means的改进算法。基于k-Means的实现和实验。-Based on the Chinese version of K-Means clustering algorithm and implementation. The main technology of Chinese Text Clustering, feature selection, shared nearest neighbor
K-Means_Text_Cluster
- K-Means文本聚类python实现，文本聚类算法，人名排除歧义-Text Cluster by the algorithm of K-means(include texts)， discrimination of name ambiguity.
ClusteringAnalysis
- java实现的K-Means文本聚类文章，采用英文撰写，需要源码的可以发邮件lixinle@yahoo.cn。-java realize the K-Means Text Clustering articles written in English to the source code can email lixinle@yahoo.cn.
DataStructTest
- K-means文本聚类方法（IDEA项目包） 下载就能运行-K-means clustering method text (IDEA project package) will be able to download Run
Kmeans
- 算法思想：提取文档的TF/IDF权重，然后用余弦定理计算两个多维向量的距离来计算两篇文档的相似度，用标准的k-means算法就可以实现文本聚类。源码为java实现(Algorithm idea: extract the TF/IDF weight of the document, then calculate the distance between two multidimensional vectors by cosine theorem, calculate the similarity