How to Whiten my data before plugging it into PCA












0















I am applying PCA to some ECG features, that I extracted. I found some code and learned it from the Matlab website, to apply PCA. However, I would like to whiten my data before applying PCA to it. My data is a matrix (125 x 9), with 9 features, and 125 tests. My matrix name is ratings.
I have two blocks of code: PCA code and whitening code. My PCA code doesn't include whitening, but I hope by answering this question, it will.



Whitening Code



I subtracted the mean of each column from the matrix, as follows:



mean_ratings=mean(ratings); %get mean of each column
ratings=ratings-repmat(mean_ratings, 375,1); %subtract mean of each
%column from each element of the column


I am a little but stuck on what to do after this. I calculated my enter image description here, by following the sample code:



sigma = ratings * ratings' / size(ratings, 2); %calculate the value of sigma
[U,S,V] = svd(sigma); %get S value and eigen vectors

xPCAwhite = diag(1./sqrt(diag(S) + epsilon)) * U' * ratings; %calculate
%whitened data


PCA Code



I perform my PCA, without considering whitening, by using the code below:



C = corr(ratings,ratings);
w=1./var(ratings);
[wcoeff,score,latent,tsquared,explained] = pca(ratings,...
'VariableWeights',w);
coefforth = inv(diag(std(ratings)))*wcoeff;
cscores = zscore(ratings)*coefforth;
figure()
plot(score(:,1),score(:,2),'+')
xlabel('1st Principal Component')
ylabel('2nd Principal Component')


Now my question is that, do I just plug in the variable 'xPCAwhite' instead of ratings for my PCA code?










share|improve this question



























    0















    I am applying PCA to some ECG features, that I extracted. I found some code and learned it from the Matlab website, to apply PCA. However, I would like to whiten my data before applying PCA to it. My data is a matrix (125 x 9), with 9 features, and 125 tests. My matrix name is ratings.
    I have two blocks of code: PCA code and whitening code. My PCA code doesn't include whitening, but I hope by answering this question, it will.



    Whitening Code



    I subtracted the mean of each column from the matrix, as follows:



    mean_ratings=mean(ratings); %get mean of each column
    ratings=ratings-repmat(mean_ratings, 375,1); %subtract mean of each
    %column from each element of the column


    I am a little but stuck on what to do after this. I calculated my enter image description here, by following the sample code:



    sigma = ratings * ratings' / size(ratings, 2); %calculate the value of sigma
    [U,S,V] = svd(sigma); %get S value and eigen vectors

    xPCAwhite = diag(1./sqrt(diag(S) + epsilon)) * U' * ratings; %calculate
    %whitened data


    PCA Code



    I perform my PCA, without considering whitening, by using the code below:



    C = corr(ratings,ratings);
    w=1./var(ratings);
    [wcoeff,score,latent,tsquared,explained] = pca(ratings,...
    'VariableWeights',w);
    coefforth = inv(diag(std(ratings)))*wcoeff;
    cscores = zscore(ratings)*coefforth;
    figure()
    plot(score(:,1),score(:,2),'+')
    xlabel('1st Principal Component')
    ylabel('2nd Principal Component')


    Now my question is that, do I just plug in the variable 'xPCAwhite' instead of ratings for my PCA code?










    share|improve this question

























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      I am applying PCA to some ECG features, that I extracted. I found some code and learned it from the Matlab website, to apply PCA. However, I would like to whiten my data before applying PCA to it. My data is a matrix (125 x 9), with 9 features, and 125 tests. My matrix name is ratings.
      I have two blocks of code: PCA code and whitening code. My PCA code doesn't include whitening, but I hope by answering this question, it will.



      Whitening Code



      I subtracted the mean of each column from the matrix, as follows:



      mean_ratings=mean(ratings); %get mean of each column
      ratings=ratings-repmat(mean_ratings, 375,1); %subtract mean of each
      %column from each element of the column


      I am a little but stuck on what to do after this. I calculated my enter image description here, by following the sample code:



      sigma = ratings * ratings' / size(ratings, 2); %calculate the value of sigma
      [U,S,V] = svd(sigma); %get S value and eigen vectors

      xPCAwhite = diag(1./sqrt(diag(S) + epsilon)) * U' * ratings; %calculate
      %whitened data


      PCA Code



      I perform my PCA, without considering whitening, by using the code below:



      C = corr(ratings,ratings);
      w=1./var(ratings);
      [wcoeff,score,latent,tsquared,explained] = pca(ratings,...
      'VariableWeights',w);
      coefforth = inv(diag(std(ratings)))*wcoeff;
      cscores = zscore(ratings)*coefforth;
      figure()
      plot(score(:,1),score(:,2),'+')
      xlabel('1st Principal Component')
      ylabel('2nd Principal Component')


      Now my question is that, do I just plug in the variable 'xPCAwhite' instead of ratings for my PCA code?










      share|improve this question














      I am applying PCA to some ECG features, that I extracted. I found some code and learned it from the Matlab website, to apply PCA. However, I would like to whiten my data before applying PCA to it. My data is a matrix (125 x 9), with 9 features, and 125 tests. My matrix name is ratings.
      I have two blocks of code: PCA code and whitening code. My PCA code doesn't include whitening, but I hope by answering this question, it will.



      Whitening Code



      I subtracted the mean of each column from the matrix, as follows:



      mean_ratings=mean(ratings); %get mean of each column
      ratings=ratings-repmat(mean_ratings, 375,1); %subtract mean of each
      %column from each element of the column


      I am a little but stuck on what to do after this. I calculated my enter image description here, by following the sample code:



      sigma = ratings * ratings' / size(ratings, 2); %calculate the value of sigma
      [U,S,V] = svd(sigma); %get S value and eigen vectors

      xPCAwhite = diag(1./sqrt(diag(S) + epsilon)) * U' * ratings; %calculate
      %whitened data


      PCA Code



      I perform my PCA, without considering whitening, by using the code below:



      C = corr(ratings,ratings);
      w=1./var(ratings);
      [wcoeff,score,latent,tsquared,explained] = pca(ratings,...
      'VariableWeights',w);
      coefforth = inv(diag(std(ratings)))*wcoeff;
      cscores = zscore(ratings)*coefforth;
      figure()
      plot(score(:,1),score(:,2),'+')
      xlabel('1st Principal Component')
      ylabel('2nd Principal Component')


      Now my question is that, do I just plug in the variable 'xPCAwhite' instead of ratings for my PCA code?







      matlab pca






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      asked Nov 26 '18 at 3:23









      MuhammadMuhammad

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