Using TF-IDF (Term Frequency - Inverse Document Frequency) values for features in a uni-gram bag-of-words model should have an effect most similar to which of the following?
A. Lowercasing the data
B. Dropout regularization
C. Removing stop words
D. Increasing the learning rate
Answer:C
Using TF-IDF (Term Frequency - Inverse Document Frequency) values for features in a uni-gram bag-of-words model should have an effect most similar to which of the following?
A. Lowercasing the data B. Dropout regularization C. Removing stop words D. Increasing the learning rate