I am studying about the pca in which I have heard about the varimax rotation but I am not able to understand how varimax rotation helps in deciding components in PCA
PCA is used to describe as much of the variation in the first few axes. Here, we first center the variables to have a mean of zero and then rotate the axes to reduce the dimensions or cover the maximum variation.
Rotation is done so that the first axis contains as much variation as possible, the second axis contains as much of the remaining variation and so on. Change of coordinates used in principal component analysis (PCA) is known as Varimax rotation. It maximizes the sum of the variances of the squared loadings as all the coefficients will be either large or near zero, with few intermediate values.
The goal is to associate each variable to at most one factor. The interpretation of the results of the PCA will be simplified.