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| Hyperparameter | Value |
|---|---|
| memory | |
| steps | [('trans', FunctionTransformer(func=<function revert_data at 0x7f3fb95883a0>)), ('vectorizer', CountVectorizer()), ('classifier', PassiveAggressiveClassifier(random_state=42))] |
| verbose | False |
| trans | FunctionTransformer(func=<function revert_data at 0x7f3fb95883a0>) |
| vectorizer | CountVectorizer() |
| classifier | PassiveAggressiveClassifier(random_state=42) |
| trans__accept_sparse | False |
| trans__check_inverse | True |
| trans__feature_names_out | |
| trans__func | <function revert_data at 0x7f3fb95883a0> |
| trans__inv_kw_args | |
| trans__inverse_func | |
| trans__kw_args | |
| trans__validate | False |
| vectorizer__analyzer | word |
| vectorizer__binary | False |
| vectorizer__decode_error | strict |
| vectorizer__dtype | <class 'numpy.int64'> |
| vectorizer__encoding | utf-8 |
| vectorizer__input | content |
| vectorizer__lowercase | True |
| vectorizer__max_df | 1.0 |
| vectorizer__max_features | |
| vectorizer__min_df | 1 |
| vectorizer__ngram_range | (1, 1) |
| vectorizer__preprocessor | |
| vectorizer__stop_words | |
| vectorizer__strip_accents | |
| vectorizer__token_pattern | (?u)\b\w\w+\b |
| vectorizer__tokenizer | |
| vectorizer__vocabulary | |
| classifier__C | 1.0 |
| classifier__average | False |
| classifier__class_weight | |
| classifier__early_stopping | False |
| classifier__fit_intercept | True |
| classifier__loss | hinge |
| classifier__max_iter | 1000 |
| classifier__n_iter_no_change | 5 |
| classifier__n_jobs | |
| classifier__random_state | 42 |
| classifier__shuffle | True |
| classifier__tol | 0.001 |
| classifier__validation_fraction | 0.1 |
| classifier__verbose | 0 |
| classifier__warm_start | False |
| Metric | Value |
|---|---|
| accuracy including 'O' | 0.903724 |
| f1 score including 'O | 0.903724 |
| precision excluding 'O' | 0.803184 |
| recall excluding 'O' | 0.525071 |
| f1 excluding 'O' | 0.635011 |
@inproceedings{...,year={2022}}