| #!/usr/bin/env python |
| # coding=utf-8 |
| |
| """MetricsEvaluator engine action. |
| |
| Use this module to add the project main code. |
| """ |
| |
| from .._compatibility import six |
| from .._logging import get_logger |
| from sklearn_crfsuite import metrics |
| from marvin_python_toolbox.engine_base import EngineBaseTraining |
| |
| __all__ = ['MetricsEvaluator'] |
| |
| |
| logger = get_logger('metrics_evaluator') |
| |
| |
| class MetricsEvaluator(EngineBaseTraining): |
| |
| def __init__(self, **kwargs): |
| super(MetricsEvaluator, self).__init__(**kwargs) |
| |
| def execute(self, params, **kwargs): |
| labels = list(self.marvin_model['crf'].classes_) |
| labels.remove('O') |
| y_pred = self.marvin_model['crf'].predict(self.marvin_dataset['X_test']) |
| |
| score = metrics.flat_f1_score(self.marvin_dataset['y_test'], y_pred, average='weighted', labels=labels) |
| |
| sorted_labels = sorted( |
| labels, |
| key=lambda name: (name[1:], name[0]) |
| ) |
| report = metrics.flat_classification_report( |
| self.marvin_dataset['y_test'], y_pred, labels=sorted_labels, digits=3 |
| ) |
| |
| self.marvin_metrics = { |
| 'score': score, |
| 'report': report |
| } |
| |
| print('Balanced F-score: ' + str(score)) |
| print('\nClassification Report: \n' + str(report)) |
| |
