| | --- |
| | {} |
| | --- |
| | ```py |
| | with open('./literary_form_classifier/model.pkl', 'rb') as fin: |
| | model = pickle.load(fin) |
| | |
| | with open('./literary_form_classifier/vectorizer.pkl', 'rb') as fin: |
| | vectorizer = pickle.load(fin) |
| | |
| | texts = ... |
| | X_infer = vectorizer.transform(texts) |
| | preds = model.predict(X_infer) |
| | ``` |
| |
|
| | Model performance on test set: |
| |
|
| | | Predicted<br>Actual | Skjønnlitteratur | Faglitteratur | Sum | |
| | |----------------------|------------------|---------------|--------| |
| | | **Skjønnlitteratur** | 12 141 | 79 | 12 220 | |
| | | **Faglitteratur** | 804 | 27 611 | 28 415 | |
| | | **Sum** | 12 945 | 27 690 | 40 635 | |
| |
|
| | Accuracy: 97.83%, F1 Score: 96.49%, Precision: 99.35%, Specificity: 99.71%, Sensitivity: 93.79%, MCC: 95.00% |
