def decision_function(self, X):
        """Evaluate the cosine similarity between document-term matrix and X.

        Parameters
        ----------
        X : array-like, shape (n_samples, n_timestamps)
            Test samples.

        Returns
        -------
        X : array-like, shape (n_samples, n_classes)
            osine similarity between the document-term matrix and X.

        """
        check_is_fitted(self, ['vocabulary_', 'tfidf_', 'idf_',
                               '_tfidf', 'classes_'])
        X = check_array(X)
        X_bow = self._bow.transform(X)
        vectorizer = CountVectorizer(vocabulary=self._tfidf.vocabulary_)
        X_transformed = vectorizer.transform(X_bow).toarray()
        return cosine_similarity(X_transformed, self.tfidf_)
Evaluate the cosine similarity between document-term matrix and X.

        Parameters
        ----------
        X : array-like, shape (n_samples, n_timestamps)
            Test samples.

        Returns
        -------
        X : array-like, shape (n_samples, n_classes)
            osine similarity between the document-term matrix and X.

        
pyts/classification/saxvsm.py