@harry wrote:
I have studied two methods one cross-validation and other is PCA.
cross-validation- It helps us to choose the tuning parameter of the model which increase the performance of the model on test data set.
PCA- It reduces the number of predictors into a manageable size and each component is the linear combination predicators .
There is always one problem in PCA to decide the number of components.What I want to know is it possible to use cross-validation for finding the number of principal components.
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