How can i use pca as a filter
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I am using PCA as filter. But as data should be obtained with maximum principle component having 90% contribution. But in my code i am not getting contribution above 90%. As i am increasing my no of observation contribution is decresing. I have used matlab function: pca(x). Please guide me what should i do to retain contribution level above 90%.
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Image Analyst
2016-3-8
Use more principal components. If you're just using the first (strongest) principal component, then yeah, it's quite possible it doesn't explain more than 90% of the variation/pattern/shape of the input observations. If you use all of them then it will explain 100%. So use as many of them as you need to reach 90%.
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Tom Lane
2016-3-11
It's not clear to me what you want. You should know that PCA thinks of the rows as observations, so a 6x4 matrix has 6 observations. The third output from PCA is the variances of the 4 components. The total of them is the total variance. By keeping all 4 you explain 100%.
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