I want to reduce the dimensionality of the BERT word embedding to, let's say, 50 dimensions. I am trying with PCA. I will use that for the document classification task.

Now for training PCA, should I train on the entire dataset by using all the word vectors from the entire data set at once that is:


or word vectors per document, that is:

for document in train_dataset:

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.