datalad-handbook/docs/usecases/_examples/ml-113
2020-09-23 14:58:50 +02:00

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Text

$ cat << EOT > code/evaluate.py
#!/usr/bin/env python3
from joblib import load
import json
from pathlib import Path
from sklearn.metrics import accuracy_score
from train import load_data
def main(repo_path):
test_csv_path = repo_path / "data/test.csv"
test_data, labels = load_data(test_csv_path)
model = load(repo_path / "model.joblib")
predictions = model.predict(test_data)
accuracy = accuracy_score(labels, predictions)
metrics = {"accuracy": accuracy}
print(metrics)
accuracy_path = repo_path / "accuracy.json"
accuracy_path.write_text(json.dumps(metrics))
if __name__ == "__main__":
repo_path = Path(__file__).parent.parent
main(repo_path)
EOT