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Sorry if I was unclear, my main goal is to plot the pca results in a way that displays the 21 points. The features were already classified into two groups before the analysis rows is one group, rows another , was just wondering how to color code them after the plot is made.
That's pretty easy. Let me post something. BTW, I think you meant columns not rows. The way you're plotting your results is that the first row denotes the first dimension while the second row is the second dimension. Add a comment. Active Oldest Votes. Hope this helps! Improve this answer. This is exactly what I wanted, I wasted a lot of time trying to figure this out so thank you very much.
Good luck! Sign up or log in Sign up using Google. However, It couldn't be understood that why de-mean is taken and what is purpose of bsxfun function? Is this function is inbuilt? Yes, bsxfun is a built-in function. It applies the element-wise operation, implicitly expanding either array, if necessary.
With more modern versions of MATLAB, implicit expansion will happen automatically, so one could actually replace that line with. Take a look at this CrossValidated answer about why centering i. Jaime de la Mota on 24 Jul This is very interesting, but a question comes to my mind. Coeffs are the eigenvectors and scores are the projection of the data in the principal component space. I don't really know, but this abstract -- I did not access or read the paper itself -- suggests that KL and PCA are not strictly equivalent.
Xiying Deng on 14 Apr What does these lines do? Thank you! These are the eigenvectors of the covariance matrix. The first line in green is a comment that describes what these lines mean. The second line. It is a numeric array in which each column is a principal component vector. The third line. I applied eig to the covariance matrix of the data, to calculate its eigenvectors.
My code shows that coeff and V are equal to each other. Thanks, you explanation is really good, I'm working with EEG data , and I cant make 'V' and 'coeff' be the same, don't really understand why, do you have any idea?
Their columns will be the same within floating-point error , but those columns will not necessarily appear in the same order.
I've edited the comments in the code above to reflect that. If that does not fix the issue, maybe you could upload your data and I could take a look. More Answers 2. Yaser Khojah on 17 Apr Dear the cyclist , thanks for showing this example. Is there anyway to see which order of these columns? In another word, what are the variables of each column? Quoting from the first section of the documentation for the pca function.
You can see that. How can I know which variables from the original data has the strength impact? Nyssa Capman on 5 Jan I believe each row of coeff corresponds to the variables, in the order they were input as. Did we forget the man What does he mean to us? To select the test picture Let's take a look at the results.
Why does brother Peng, who has sharp edges and corners, become a greasy uncle??? You will understand that PCA will select the image training set output that is closest to the European distance of the input image test set data based on the data characteristics of the average face. Therefore, we have to admit that this uncle's facial data is the "most suitable" facial data feature of the male god.
Wang is Yale University's open-source face data.
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