Why we normalize the loading's of the principal component?

pca

#1

I am studying about the dimension reduction in which I am studying about principal component analysis while studying it I came across that each component is the linear combination of the features .The basis is called loadings and I came to know that the loadings need to be standardized before using .I want to know that why it is necessary to normalize the loadings before creating the component.


#2

Hi Ankit

The principal components are supplied with normalized version of original predictors. This is because, the original predictors may have different scales. For example: Imagine a data set with variables’ measuring units as gallons, kilometers, light years etc. It is definite that the scale of variances in these variables will be large.

Performing PCA on un-normalized variables will lead to insanely large loadings for variables with high variance. In turn, this will lead to dependence of a principal component on the variable with high variance. This is undesirable.

Regards,
Tony