搜索资源列表
EM
- EM 算法MATLAB代码，用于数据聚类。-em algorithm which is used in data clustering.
kmeans
- 基本的数据聚类算法，可以进行快速有效的数据聚类，可以有效地进行数据挖掘-Basic data clustering algorithm, can be fast and effective data clustering, data mining can be effectively
KNN
- 数据挖掘导论中的K近邻聚类算法，用C++编写而成。-Introduction to Data Mining of the K neighbors clustering algorithm, using C++ has been prepared by.
Wallpapers-based-on-mean-shift
- 本程序首先把图像由RGB空间转到HSI空间，然后利用彩色图像分割策略以及meanshift算法对图像进行分割最后加入边界合成。其中‘keyprogram.m’文件为主程序，‘meanshift.m’文件为调用函数，实现数据的聚类分割。-The program first the image from the RGB space to HSI space and then using color image segmentation strategy and meanshift image seg
fuzzyPR
- 模糊聚类的经典算法，可以使用UCI数据集进行聚类，该程序附有详细的说明-Classical fuzzy clustering algorithm, you can use the UCI data sets clustering, the program is accompanied by a detailed descr iption of
text-data-mining
- 此程序实现了如何在TXT或WORD文档中进行数据挖掘,在文本中提取有用信息-The realization of this procedure how to TXT or WORD document to carry out data mining, in the text to extract useful information
NcutClustering_7
- Data Clustering with Normalized Cuts
moshishibie
- 先用C-均值聚类算法程序，并用下列数据进行聚类分析。在确认编程正确后，采用蔡云龙书的附录B中表1的Iris数据进行聚类。然后使用近邻法的快速算法找出待分样本X（设X样本的4个分量x1=x2=x3=x4=6；子集数l=3）的最近邻节点和3-近邻节点及X与它们之间的距离。-First C-means clustering algorithm procedures and with the following data for cluster analysis. After confirming t
Cluster
- 使用分解聚类算法在IRIS数据上进行聚类分析，IRIS数据是由鸢尾属植物的三种单独的花的测量结果所组成，模式类别数为3，特征维数是4，每类各有50个模式样本，总共有150个样本。-The use of decomposition in the IRIS data clustering algorithm on the cluster analysis, IRIS data are from the iris flower three separate components of the meas
CLICKS
- clique code with sample data set. clique is a data clustering algorithm which follows hierarchical clustering method.
clustering
- To identify distinguishable clusters of data in an n-dimensional pixel value image. Given: Samples of multi-spectral satellite images -To identify distinguishable clusters of data in an n-dimensional pixel
hddc_toolbox_1.0
- The High Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifiers for high-dimensional data. This classifier is based on Gaussian models adapted for high-dimensional data. Reference: C. Bouveyron, S. Girard and
clustering
- Fuzzy Clustering. Problem: To extract rules from data Method: Fuzzy c-means Results: e.g., finding cancer cells
iso data
- ISODATA聚类算法，内附详细注解，使用了Iris数据集。ISODATA是一种常用的聚类算法之一。-ISODATA clustering algorithm, containing detailed notes, using the Iris data set. ISODATA clustering algorithm is a common one.
clustering-2009
- 本书是有关数据挖掘技术聚类方面的经典书籍。-This book is about the aspects of data mining clustering classic books.
clustering-presentations
- This package contains presentations and pdfs related to data clustering.Some of the algorithms discussed in this zip file are kmeans,cure-This package contains presentations and pdfs related to data clustering.Some of the algorithms discussed in this
clustring
- clustring(Density-Based Spatial Clustering of Applications with Noise) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jö rg Sander and Xiaowei Xu in 1996.[1] It is a density-based clustering algorithm because it find
Clustering
- 能够对股票数据进行聚类，而且是根据趋势相似性进行分类-Able to share data, clustering, and is classified based on trends and similarities
Data-Clustering-with-Normalized-Cuts
- Data clustering using graph cut method
Data-Clustering-with-Normalized-Cuts
- 用ncut算法做的数据聚类，经过测试可以正常使用-data clustering with NCUT