This is an update of my previous article on Principal Component Analysis in R & Python. After having received several request on describing the process of model building with principal components, I’ve added an exclusive section of model building in R.
I came to know that R users often lost their way after doing PCA on train set. They become indecisive of next step i.e. how to use these components to make predictions on test data. I hope this article would help you understand PCA in detail and use it more frequently in your daily modeling process.
Don’t forget to drop in your suggestions / opinions on this topic. Even if you find any part of PCA difficult to understand, you can ask me below.