Gaussian mixture model--maximum likelihood
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I have 3 classes and I modeled the GMM for those classes with 12 components for each model.
Now I have a data from one of the 3 classes. I want to find out the class that the data belongs to. I tried finding out the likelihood but I don't know how to proceed next to make the decision.
I have about 12 likelihood values for each class. What should I do next?
回答（4 个）
Walter Roberson
2011-10-16
编辑：John Kelly
2015-2-27
0 个投票
I would suggest reading the File Exchange contribution http://www.mathworks.com/matlabcentral/fileexchange/18785
3 个评论
i Venky
2011-10-16
i Venky
2011-10-16
Walter Roberson
2011-10-17
What happened when you tried that file?
I never make a statement about which technique is "best" for something. There are always other techniques that I haven't heard of, or perhaps which have not been invented yet, or which might happen to be faster or more accurate for your *particular* situation even if they are provably less accurate in general. The concept of "best" means different things to different people. For example, you probably would not think very much of a technique that could promise 100% accuracy but took 17.89 million years to execute.
i Venky
2011-10-17
0 个投票
3 个评论
Walter Roberson
2011-10-17
My team of substitute sleepers get Sunday evening off, so I have to do the sleeping myself.
i Venky
2011-11-4
Jan
2011-11-4
@i Venky: Walter asked: "What happened when you tried that file?"
Walter Roberson
2011-11-4
0 个投票
What you should do is apply a distance function to find the "distance" between any given sample and the centroids of the 3 classes. The class with the lowest distance has the greatest probability of being the class the sample is a member of.
A simple distance function is Euclidean distance. It is not used that much in classification questions: instead more common is to use a metric that takes in to account the covariance matrices. For example, using the Anderson-Bahadur metric is common.
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2015-2-27
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