# select majority class of each instance (row) dev_predictions = [] for row in dev_preds: row = row.tolist() dev_predictions.append(int(max(set(row), key=row.count))) # select majority class of each instance (row) test_predictions = [] for row in test_preds: row = row.tolist() test_predictions.append(int(max(set(row), key=row.count))) dev["predictions"] = dev_predictions print("Precision: ", precision(dev['labels'].tolist(), dev['predictions'].tolist())) print("Recall: ", recall(dev['labels'].tolist(), dev['predictions'].tolist())) print("F1: ", f1(dev['labels'].tolist(), dev['predictions'].tolist())) tn, fp, fn, tp = confusion_matrix_values(dev['labels'].tolist(), dev['predictions'].tolist()) print("Confusion Matrix (tn, fp, fn, tp) {} {} {} {}".format(tn, fp, fn, tp)) converted_test_predictions = decode(test_predictions) with open(os.path.join(TEMP_DIRECTORY, SUBMISSION_FILE), 'w') as f: for item in converted_test_predictions: f.write("%s\n" % item)
print("Completed Fold {}".format(i)) # select majority class of each instance (row) ara_test_final_predictions = [] for row in ara_dev_preds: row = row.tolist() ara_test_final_predictions.append(int(max(set(row), key=row.count))) ara_dev["predictions"] = ara_test_final_predictions print("--------------Arabic--------------") print("Precision: ", precision(ara_dev['labels'].tolist(), ara_dev['predictions'].tolist())) print("Recall: ", recall(ara_dev['labels'].tolist(), ara_dev['predictions'].tolist())) print("F1: ", f1(ara_dev['labels'].tolist(), ara_dev['predictions'].tolist())) tn, fp, fn, tp = confusion_matrix_values(ara_dev['labels'].tolist(), ara_dev['predictions'].tolist()) print("Confusion Matrix (tn, fp, fn, tp) {} {} {} {}".format(tn, fp, fn, tp)) # select majority class of each instance (row) bul_test_final_predictions = [] for row in bul_dev_preds: row = row.tolist() bul_test_final_predictions.append(int(max(set(row), key=row.count))) bul_dev["predictions"] = bul_test_final_predictions print("--------------Bulgarian--------------") print("Precision: ",