Making Predictions on Test Data after Principal Component Analysis in R
avcontentteam —
Published On July 28, 2016 and Last Modified On August 26th, 2021
Introduction
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.
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One thought on "Making Predictions on Test Data after Principal Component Analysis in R"
Afreen Begum says: August 02, 2016 at 3:41 pm
Hi, I would like to know that after doing PCA On train set how can i use these components for prediction and i want to find weightages of attributes after doing PCA. how can i proceed for giving weightages to the attributes after doing PCA????