mpi_kmeans
所属分类：模式识别(视觉/语音等)
开发工具：matlab
文件大小：70KB
下载次数：68
上传日期：2010-02-04 08:50:58
上 传 者：
huazehuang
说明： K means K均值算法 K means K均值算法 K means K均值算法 K means K均值算法
(K means K means algorithm K means K means algorithm K means K means algorithm K means K means algorithm)
文件列表:
mpi_kmeans (0, 2009-07-14)
mpi_kmeans\mpi_assign.cxx (734, 2008-02-14)
mpi_kmeans\mpi_kmeans_mex.cxx (3013, 2008-02-14)
mpi_kmeans\mpi_kmeans_ordinary.cxx (5830, 2007-12-19)
mpi_kmeans\mpi_kmeans.h (1251, 2008-02-14)
mpi_kmeans\mpi_kmeans.cxx (13339, 2008-02-14)
mpi_kmeans\Makefile (1082, 2008-02-17)
mpi_kmeans\LICENSE-2.0.txt (11358, 2008-02-14)
mpi_kmeans\mpi_kmeans.py (1573, 2008-02-14)
mpi_kmeans\mpi_kmeans.m (2665, 2008-02-14)
mpi_kmeans-1.5 (0, 2009-07-14)
mpi_kmeans-1.5\Changelog (392, 2009-04-07)
mpi_kmeans-1.5\mpi_kmeans_mex.cxx (3536, 2009-04-07)
mpi_kmeans-1.5\mpi_kmeans.h (908, 2009-04-07)
mpi_kmeans-1.5\test_code.m (2157, 2009-04-07)
mpi_kmeans-1.5\mpi_kmeans_mex.h (1122, 2009-04-07)
mpi_kmeans-1.5\example.txt (39, 2009-04-07)
mpi_kmeans-1.5\py_kmeans.c (84513, 2009-04-07)
mpi_kmeans-1.5\py_kmeans.pyx (2533, 2009-04-07)
mpi_kmeans-1.5\mpi_kmeans.cxx (15888, 2009-04-07)
mpi_kmeans-1.5\Makefile (2953, 2009-04-07)
mpi_kmeans-1.5\LICENSE-2.0.txt (11358, 2009-04-07)
mpi_kmeans-1.5\mpi_kmeans.py (1573, 2009-04-07)
mpi_kmeans-1.5\mpi_assign_main.cxx (5171, 2009-04-07)
mpi_kmeans-1.5\py_kmeans.so (48868, 2009-07-14)
mpi_kmeans-1.5\mpi_kmeans_main.cxx (7805, 2009-04-07)
#
# About
#
This k-means clustering code is a mex implementation of the ICML2003 paper
@misc{ elkan03using,
author = "C. Elkan",
title = "Using the triangle inequality to accelerate kMeans",
text = "C. Elkan. Using the triangle inequality to accelerate kMeans. In Proceedings
of the Twentieth International Conference on Machine Learning, 2003, pp.
147-153.",
year = "2003",
url = "citeseer.ist.psu.edu/elkan03using.html"
}
#
# Installation
#
You need to update the Makefile if you are on a ***bit machine (you will see it). and to give the correct
$MATLABDIR if you want to use matlab. Then call "make clean all shared"
Or within Matlab, using mex:
mex -cO mpi_kmeans.cxx
mex -O mpi_kmeans_mex.cxx mpi_kmeans.o
mex -O mpi_assign.cxx mpi_kmeans.o
If you are fine with single precision you can update the variable INPUT_TYPE in mpi_kmeans.h
#
# Use
#
Matlab:
Try "help mpi_kmeans" in a matlab shell. This will also give an example
Python:
Just run ./mpi_kmeans.py for an example.
Tuebingen, 14th Feb 2008
Peter Gehler, peter.gehler@tuebingen.mpg.de
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