I have a dataset which contains both text and numeric features.
I have encoded the text ones using the TfidfVectorizer from sklearn.
I would now like to apply logistic regression to the resulting dataframe.
My issue is that the numeric features aren't on the same scale as the ones resulting from tfidf.
I'm unsure about whether to:
scale the whole dataframe with StandardScaler prior to passing to a classifier;
only scale the numeric features, and leave the ones resulting from tfidf as they are.