Using Principle Component Analysis (PCA) in classification

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KaMu 2014-6-24

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https://ww2.mathworks.cn/matlabcentral/answers/137422-using-principle-component-analysis-pca-in-classification

评论： jin li 2018-7-13

Hi All, I am working in a project that classify certain texture images. I will be using Gaussian Mixture model to classify all the database into textured and non-textured images.

Now, I am using PCA to reduce the dimension of my data that is 512 dimensions, so I can train the GMM model. The results from PCA are new variables and those variables will be used in the training process:

[wcoeff,score,latent,~,explained] = pca(AllData);

The question is: in the testing process how can I use the wcoeff to get the same variables? Do I just multiply the wcoeff with the new image?

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Delsavonita Delsavonita 2018-5-8

编辑：Adam 2018-5-8

i have the same problem too, since you post the question on 2014, you must be done doing your project, so can you kindly send me the solution for this problem ? i really need this...