Machine Learning, Data Science, NLP, Dimensionality Reduction, Pca.
100,000 features of Tfidf vectorizer. However, these 200-dimensional vectors are dense matrices with all real numbers, while 100,000 features are sparse matrices with lots of zeros. Thus in terms of computation, Doc2Vec vectors also take a bit of time for computation. So if I can reduce dimensions,