In statistics, machine learning, and information theory, dimensionality reduction or dimension reduction is the procedure of reduce the number of random variables under consideration by obtaining a set of principal variables. Approaches can be divided into feature choice and feature extraction.

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```
library(stats)
pca <- princomp(train, cor = TRUE)
train_reduced <- predict(pca,train)
test_reduced <- predict(pca,test)
```