I have a 10 components and would like to know the loading of each component (from 56 variables used)
as I use pca.components_ and compare the highest correlation score with all 56 variables, there are several components that didn't get its loadings.
is it because I didn't do : pca.components_.T * np.sqrt(pca.explained_variance_) ?
How we can get rotated component matrix in Python (as we get like output in SPSS)?
The things I ask more into visualization of loadings for PCA. Which I find out that it was a set of array as explained in https://datascience-enthusiast.com/Python/PCA_Spark_Python_R.html
and loadings itself is actually pca.component_