HashingVectorizer is a Python class within the sklearn.feature_extraction.text module that performs feature extraction on text data using the hashing trick. This vectorizer converts a collection of text documents into a matrix representation, where each document is represented as a set of hashed words. The advantage of using HashingVectorizer is that it requires less memory compared to other vectorizers, as it applies a hash function to the word occurrences and directly maps them to the feature indices. This makes it suitable for processing large datasets and online learning scenarios.
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