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Principal Components Regression (PCR) is a technique for analyzing multiple regression data that suffer from multicollinearity. Principal components regression reduces errors in regression estimates by adding a degree of bias
The Principal Component Analysis is a popular unsupervised learning algorithm that is widely known for dimensionality reduction. It increases the interpretability and also reduces the loss of information while reducing the dimensionality.
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