NcutClustering_7
所属分类：人工智能/神经网络/深度学习
开发工具：matlab
文件大小：49KB
下载次数：24
上传日期：2006-01-01 11:23:08
上 传 者：
xujianjiang
说明： 一个数据挖掘的分类算法，Normalizedcluster
(a classification of data mining algorithms, Normalizedcluster)
文件列表:
common_files\a_times_b_cmplx.dll (7114, 2004-06-18)
common_files\a_times_b_cmplx.mexglx (7820, 2004-06-18)
common_files\a_times_b_cmplx.mexmac (13096, 2004-06-18)
common_files\discretisation.m (1251, 2004-06-18)
common_files\discretisationEigenVectorData.asv (202, 2004-06-18)
common_files\discretisationEigenVectorData.m (317, 2004-06-18)
common_files\eigs2.m (37466, 2004-06-18)
common_files\mex_w_times_x_symmetric.dll (9728, 2004-06-18)
common_files\mex_w_times_x_symmetric.mexglx (8713, 2004-06-18)
common_files\mex_w_times_x_symmetric.mexmac (13396, 2004-06-18)
common_files\ncut.asv (2339, 2004-06-18)
common_files\ncut.m (2470, 2004-06-18)
common_files\ncutW.asv (486, 2004-06-18)
common_files\ncutW.m (604, 2004-06-18)
common_files\sparsifyc.dll (8704, 2004-06-18)
common_files\sparsifyc.mexglx (8541, 2004-06-18)
common_files\sparsifyc.mexmac (9004, 2004-06-18)
common_files\spmtimesd.dll (7168, 2004-06-18)
common_files\spmtimesd.mexglx (7285, 2004-06-18)
common_files\spmtimesd.mexmac (8888, 2004-06-18)
demoNcutClustering.m (1176, 2004-06-18)
main.m (309, 2004-06-18)
specific_NcutClustering_files\build_scene.m (3259, 2004-06-18)
specific_NcutClustering_files\compute_relation.m (594, 2004-06-18)
Version.txt (284, 2004-06-18)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Normalized Cut Clustering Code %
% %
% Timothee Cour (UPENN), Stella Yu (Berkeley), Jianbo Shi (UPENN) %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Installation Notes :
1) After you unzipped the files to mydir,
put the Current Directory in Matlab to mydir
2) In the matlab command prompt,
type demoNcutClustering to see a demo
or...
type main to initialize the paths to subfolders
3) You can now try any of the functions
The files were tested under matlab 6.5
Top level functions:
ncutW: Given a similarity graph "W", computes Ncut clustering on the graph into "ncCluster" groups;
NcutDiscrete = ncutW(W,nbCluster);
Use demo.m to see how to use the clustering function.
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