搜索资源列表
SimpleKMeans
- kmeans.java 代码。用于数据挖掘中的聚类算法。这个事weka中开源的代码。-failed to translate
java
- 解决数据聚类分离问题，用java能很好的解决这一问题，提高效率 对大家有帮助-Solve the problem of separation of data clustering, java can be used to solve this problem well, to improve efficiency to help everyone
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
java-kmeans
- 用java实现的聚类算法kmeans，可以用eclipse直接运行。-Clustering algorithm implemented with java
carrot2-java-api-3.5.0
- java聚类的开源资料，可以直接生成数据集，然后调用该聚类，对数据集进行聚类-java open source data clustering, can generate data sets, and then call the clustering, clustering of data sets
src
- 聚类算法实现，基于密度的聚类算法，该算法能够用于对数据进行基于密度的分类-Clustering algorithm, density-based clustering algorithm, which can be used for data classification based on density
MessageClustering
- 用java实现的应用了weka包的Kmeans方法的文本聚类程序。-a program written in java with simplekmeans in weka.jar.
DocCluster
- 实现的文档聚类的JAVA程序，适宜入门。-Implementation document clustering JAVA program, suitable for entry.
wekaUT.tar
- 实现半监督聚类，针对weka框架进行扩展。-It realize semi-supervised clustering method. And it is extension of weka.
SimpleKMeans
- 数据挖掘中经典的k means聚类算法实现-kmeans cluster
Algorithms-of-the-intelligent-web
- 智能web算法英文原版, 描述利用各种技术对web应用进行智能化的处理； 涵盖五类重要算法：搜索、推荐、聚类、分类和分类器融合-This is the English original version of <Algorithms of the Intelligent Web>. It is about the use of techniques that enable the intelligent processing of information.This
DBSCAN
- DBSCAN算法的Java实现 DBSCAN是一种基于密度的聚类算法，它的根基事理就是给定两个参数，ξ和minp，其中 ξ可以理解为半径，算法将在这个半径内查找样本，minp是一个以ξ为半径查找到的样本个数n的限制前提，只要n>=minp，查找到的样本点就是焦灯揭捉
k-means-in-java
- k-means算法的java描述，用java语言编写的k-means算法，用于聚类和分类-K-means algorithm java is described, using java language k-means algorithm, for clustering and classification
MatchingEngine
- 用java写的分类聚类算法 用java写的分类聚类算法 -The classification of writing with Java clustering algorithm
myKMedoids
- 基于KMedoids聚类算法的java实现 包含myKMedoids程序，测试数据 另包含生成数据的小程序 -java archive based on KMedoids clustering algorithm contains myKMedoids program, test data and another small program that generated datas
K_means
- 一个实现K中心聚类的算法源码，java实现-An implementation of the K-center clustering algorithm
TextClustering
- 文本聚类算法包含 tfidf的实现 k-means算法的实现-Text clustering algorithm contains tfidf implementation of the k-means algorithm to achieve
mahy
- 基于相对密度的聚类算法（DBSCAN算法），用于处理高密度簇完全被相连的低密度簇所包含的问题-Clustering algorithm based on relative density (DBSCAN algorithm), to handle high-density clusters are completely connected to the problem of low-density cluster contains
chameleon
- JAVA实现变色龙chameleon算法，CHAMELEON是一种两阶段聚类法。第一阶段把点分成很多小的簇；第二阶段根据相近程度合并这些小的簇。-JAVA realization a chameleon chameleon algorithm, CHAMELEON clustering method is a two-stage. The first phase of the point divided into many small clusters these small clusters
Kmeans1
- 连接mysql数据库的k均值聚类算法，有想过还不错。-connect with mysql by k_means。Great result.