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Partial Least Squares in R (Step-by-Step)

statology.org · 1,144 words · saved by 1 readers

This tutorial explains how to perform partial least squares in R, including a step-by-step example.

One of the most common problems that you’ll encounter in machine learning is multicollinearity. This occurs when two or more predictor variables in a dataset are highly correlated. When this occurs, a model may be able to fit a training dataset well but it may perform poorly on a new dataset it has never seen because it overfits the training set. One way to get around this problem is to use a method known as partial least squares, which works as follows: Standardize both the predictor and response variables. Calculate M linear combinations (called “PLS components”) of the original p…

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