Forked from loretoparisi/fasttext_confusion_matrix.py
Created
November 5, 2018 15:39
-
-
Save okd-hkd/3738082cc9e6a94d8da9097fdf44be7e to your computer and use it in GitHub Desktop.
Calculate FastText Classifier Confusion Matrix
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| #!/usr/local/bin/python3 | |
| # @author cpuhrsch https://github.com/cpuhrsch | |
| # @author Loreto Parisi loreto@musixmatch.com | |
| import argparse | |
| import numpy as np | |
| from sklearn.metrics import confusion_matrix | |
| def parse_labels(path): | |
| with open(path, 'r') as f: | |
| return np.array(list(map(lambda x: x[9:], f.read().split()))) | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser(description='Display confusion matrix.') | |
| parser.add_argument('test', help='Path to test labels') | |
| parser.add_argument('predict', help='Path to predictions') | |
| args = parser.parse_args() | |
| test_labels = parse_labels(args.test) | |
| pred_labels = parse_labels(args.predict) | |
| eq = test_labels == pred_labels | |
| print("Accuracy: " + str(eq.sum() / len(test_labels))) | |
| print(confusion_matrix(test_labels, pred_labels)) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment