random_forest_classifier.py 文件源码

def learn_structure(self, samples):
        X_train, X_train_label, X_test, X_test_label = \
            self._generate_train_test_sets(samples, 0.75)
        logger.info('Training with ' + str(len(X_train)) +
                    'samples; testing with ' + str(len(X_test)) + ' samples.')

        rf_detector = self._get_best_detector(X_train, X_train_label)
        Y_test = rf_detector.predict(X_test)

        num_anomalies = Y_test[Y_test == ANOMALY].size
        logger.info('Found ' + str(num_anomalies) +
                    ' anomalies in testing set')

        logger.info('Confusion Matrix: \n{}'.
                    format(classification_report(
                        X_test_label,
                        Y_test,
                        target_names=['no', 'yes'])))
        return rf_detector