搜索资源列表
fcluster-1[1].2g.tar
- 模糊聚类的算法实现程序，用java实现，源代码-fuzzy clustering algorithm procedures, using java achieved, the source code
kmeans_java
- k-means聚类算法的java代码实现,良好的代码风格，适合扩充-k-means clustering algorithm to achieve the java code, the code of good style, suitable for expansion
MyTest
- 利用wvtool实现文本分类的实例程序,自己写的，功能简单-Text Classification using wvtool instances of programs to achieve their own writing, feature a simple
5956446fmap1
- programm clustering map with java for indexing donné
data_generator
- Java applet that allows to create a customised spatial data set for clustering, by clicking with the mouse in a panel. Data coordinates appear in the right box and a matrix of Euclidean/ cosine distances between the points can be calculated by select
clustream_mtc_cx
- 流聚类算法，利用JAVA语言实现，简单实用。-Stream clustering algorithm, using JAVA language implementation, simple and practical.
tech-rep5.ps
- 最新的多目标聚类的JAVA程序 IEEE EC上的文章所需要的程序 十分推荐给大家-Multi-objecitve clustering code for data mining
gainianshucode
- 这是用Java实现的概念树聚类的代码，是数据挖掘中的重要部分。-This is the realization of the concept of using Java code tree clustering is an important part of data mining.
kmeansclustering
- this is java program which can be used for cluster the data using kmeans clustering
DocumentCluster
- clustering k-mean java
CarolCluster
- 用Java实现聚类算法， 用Java实现聚类算法-Clustering algorithms with Java implementation, using Java to achieve clustering algorithm, clustering algorithm with a Java implementation
mallet-2.0.6
- 关于自然语言处理、机器学习的一个开源软件。-MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, clustering, information extraction, and other machine learning applications to text.
cluster
- The package aims at providing an implementation of k-means Clustering Algorithm in Java. The package does not provide for any UI and it is up to the user to display the output in the required format.
textcluster
- 文本聚类 预处理+KMeans的Java程序-Clustering preprocessing+ KMeans the Java program
k-means
- k-means聚类算法的描述及java实现-k-means clustering algorithm to achieve the descr iption and the java
attachments
- K Means clustering with multiple attributes taken differently
mwiry
- Sampling from a priori probability, calculate the weight, Can dynamically adjust the parameters of the operating environment, Using MATLAB dynamic clustering or iterative self-organizing data analysis.
CLIQUE
- CLIQUE（Clustering In QUEst)是一种简单的基于网格的聚类方法，用于发现子空间中基于密度的簇。CLIQUE把每个维划分成不重叠的区间，从而把数据对象的整个嵌入空间划分成单元。它使用一个密度阈值识别稠密单元和稀疏单元。一个单元是稠密的，如果映射到它的对象数超过该密度阈值。(CLIQUE (Clustering In QUEst) is a simple grid based clustering method for the discovery of clusters bas
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