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One option is to scikit-learn's sklearn.impute.IterativeImputer. initial_strategy could be set to "most_frequent" which a useful way to model the Bernoulli distrubtion of the features.


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It totally depends on what sort of feature engineering you use. Except for the case of KNN which is useless. Naive Bayes will work well with Bag of Words and TF-IDF while Logistic regression will perform well on all including Word2Vec.


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