# 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)
# 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: ",
precision(bul_dev['labels'].tolist(), bul_dev['predictions'].tolist()))
print("Recall: ",
recall(bul_dev['labels'].tolist(), bul_dev['predictions'].tolist()))
