Description: This is a function performs maximum likelihood estimation of Gaussian mixture model by using expectation maximization algorithm.
It can work on data of arbitrary dimensions. Several techniques are applied in order to avoid the float number underflow problems that often occurs on applying probability analysis on high dimensional data. Speed is another major concern which is optimized by vertorization and matrix factorization.
This is a widely used algorithm. The detail of this algorithm can be found in any textbook or tutorial. Just google EM Gaussian Mixture or you can find it here
http://en.wikipedia.org/wiki/Expectation-maximization_algorithm
This function is robust and speedy yet the code structure is very clear. The code is easy to read.
example:
load data;
label = emgm(x,3);
spread(x,label);
MATLAB release MATLAB 7.9 (2009b)
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用EM算法估计Gaussian mixture model(GMM)参数
共6个文件
m:3个
txt:2个
mat:1个
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2012-03-23
20:37:50
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用EM方法求GMM模型的极大似然估计,可以对任意维数的数据进行处理
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EM algorithm for Gaussian mixture model(GMM).zip (6个子文件)
spread.m 915B
license.txt 1KB
logsumexp.m 481B
emgm.m 3KB
data.mat 15KB
readme.txt 874B
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- yangxiazai2015-01-13没有试出来,还是下载了
- guaiguaishou2013-11-23试试看 貌似不能运行成功
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