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When testing my classifiers with new data, should I

  • remove stopwords from this data and/or
  • remove low information features from this data?

or just use the data the way it is?

In other words: Is removing stopwords and low information features only relevant for the data that I use to train and test the classifier or also for the data that the classifier will then classify?

Thanks!

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remove stopwords from this data

It depends on many things, such as the classifier and the features. E.g. it is quite common to remove stopwords when using bag-of-words, but very uncommon when using recurrent neural networks.

remove low information features from this data

People often use the validation set to explore feature selection.

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  • $\begingroup$ Thanks for your answer. I am using the bag of words model, so I should remove stopwords form the yet-to-classify data as well. I don't quite understand your other answer. I was not talking about the validation set, I was refering to completely new data. I have already trained and tested my classifier. $\endgroup$ – user3813234 Oct 24 '16 at 12:09

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