搜索资源列表
weka-src.rar
- Weka，一个数据挖掘工具。功能包括：分类、聚类和关联规则等等。这是该开源软件的源代码，版本为3.5.7,Weka, a data mining tool. Features include: classification, clustering and association rules, etc.. This is the open source software source code, version 3.5.7
K-Means-Dynamic-clustering
- K-means 动态聚类算法（Dynamic clustering algorithm）源程序-Dynamic clustering algorithm of K-means
_data.tar
- 实现三维点云条件欧式聚类，附带点云数据和CMakelists文件(Three dimensional cloud conditions to achieve the European clustering, with cloud data and CMakelists files)
AggloCluster
- hierarchical clustering
Hierarchical-clustering-Algorithm-master
- clustering in matlab
clustering
- 包括层次聚类和密度聚类的效果对比，是机器学习入门的好东西(Including hierarchical clustering and density clustering effect contrast, is a good machine learning entry)
Clustering_toolbox
- clustering toolbox.pattern recognation
kmeans_fast_Color
- clustering toolbox easy to use
ffcmw
- clustering toolbox. fast color kmean
Density-ratio 1.1
- clustering using density ratio
PSO_clustering
- pso for data clustering program. v v helpful
DBSCAN Clustering
- 基于matlab的dbscancluster的实现可用于文本聚类(The implementation of dbscancluster based on Matlab can be used for text clustering)
Rank-Order-Distance-based-clustering
- rank order distance based clustering for clustering same face images.
f201708201503229995
- clustering in matlab with power full source
BBPSO
- BBPSO clustering for data bases like iris, vowel, cancer, etc.
kmedia
- 利用所编的程序，完美的实现经典的K-means聚类算法分析。(Using the program compiled, the classic K-means clustering algorithm is realized perfectly.)
K-mean Clustering and RBF _V_1.0
- Radial Basis Function with K Mean Clustering using Pseudo inverse method
Self-weighted Multiview Clustering
- Self-weighted Multiview Clustering with Multiple Graphs
Clustering
- 1) 使用凝聚型层次聚类算法（即最小生成树算法）对所有数据点进行聚类，最后聚成3类。相异度定义方法可选择single linkage、complete linkage、average linkage或者average group linkage中任意一种。 2) 使用C-Means算法对所有数据点进行聚类。C=3。 任务2（必做）： 使用高斯混合模型（GMM）聚类算法对所有数据点进行聚类。C=3。并请给出得到的混合模型参数（包括比例??、均值??和协方差Σ）。 任务3（全做）： 1) 参考数据文
Subtractive-Clustering-Algorithm-master
- 能够实现减法聚类，通过减法聚类对数据进行分类，使用python编程(It can realize subtraction clustering and use Python Programming)