TfidfVectorizer.fit_transform is a method in the sklearn.feature_extraction.text module of Python's scikit-learn library. It is used to convert a collection of raw documents into a matrix of TF-IDF (Term Frequency-Inverse Document Frequency) features. This method both fits the model to the given data and transforms it. It calculates the TF-IDF values for each term in the documents and returns a sparse matrix representation of the transformed data. The TF-IDF values measure the importance of each term in a document relative to a collection of documents, providing a numerical representation of the textual data for further analysis or machine learning tasks.
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