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* [Predefined and custom stopwords removal](https://en.wikipedia.org/wiki/Stop_words)
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* [Word-based or character-based Ngram extraction and SkipGram extraction (through the advanced [options](xref:Microsoft.ML.Transforms.TextFeaturizingEstimator.Options.WordFeatureExtractor))](https://en.wikipedia.org/wiki/N-gram)
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* [Word-based or character-based Ngram extraction and SkipGram extraction](https://en.wikipedia.org/wiki/N-gram) (through the advanced [options](xref:Microsoft.ML.Transforms.TextFeaturizingEstimator.Options.WordFeatureExtractor))
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* [TF, IDF or TF-IDF](https://en.wikipedia.org/wiki/Tf%E2%80%93idf)
By default the features are made of (word/character) n-grams/skip-grams and the number of features are equal to the vocabulary size found by analyzing the data.
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To output an additional column with the tokens generated, use [OutputTokensColumnName](xref:Microsoft.ML.Transforms.Text.TextFeaturizingEstimator.Options.OutputTokensColumnName).
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