Principal component Analysis example on Matlab
3 ビュー (過去 30 日間)
古いコメントを表示
I think there is something wrong here. I am applying the PCA through the statistical tool. I have a data XData that range from 1-0.9 with 512 dimension. I am using the PCA to reduce the dimension. I was following the example on: http://www.mathworks.com/help/stats/feature-transformation.html#f75476
I have applied : [coeff,score,latent] = pca(XData);
Then to transform the coefficients so they are orthonormal :
coefforth = inv(diag(std(XData)))*wcoeff;
when I test the data using : cscores = zscore(XData)*coefforth;
I can see that cscores and score are both different. Note that I didn’t need to wight my data.
I have also tried with a new data set :
0 件のコメント
回答 (0 件)
参考
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!