I am having an issue where some classes have a 0% or <60% success rate given the training set. I was given a list of words to help classify data like this, but I am not sure how to do so. I know stop words remove certain words from the data, but can you apply a list of words to a certian class that can help the ML algo determine a better result?
Using CountVectorizer or TfidfVectorizer, can you do the opposite of stop words, but to apply certain words to a classification?
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I think you're looking for the
vocabulary
parameter of the vectorizers. For example, here's a minimal example withCountVectorizer
that only uses the words "one" and "two."If you don't know what words to use ahead of time, another approach would be to do feature selection on the outputs of a vectorizer.