Is there a way to prioritize or increase feature importance while training a ML model for classifying textual data?
I have a textual data set, containing product description. I need to classify these descriptions into different products. I am using TFIDF vectorization to vectorize the tokens into features for training. For any target label, is there a way to prioritize or increase or decrease the importance of certain features or words?