Searching experiment results
MLflow makes it easy to query the results of your experiments, helping you track model performance and hyperparameters.
Let's examine your most recent experiment, finding the model with the lowest Mean Absolute Percentage Error (MAPE).
이 연습은 강의의 일부입니다
Designing Forecasting Pipelines for Production
연습 안내
- Search MLflow runs by the
experiment_name. - Get the single best-performing model from
all_resultsbased onmetrics.mape. - Print the subset of
best_mape_model.
실습형 인터랙티브 연습
이 예제를 이 샘플 코드를 완성하여 풀어보세요.
experiment_name = "hyperparameter_tuning"
# Search MLflow runs
all_results = mlflow.____(experiment_names=[____])
# Filter for the model with the best MAPE score
best_mape_model = all_results.____("metrics.mape").head(____)
# Print the model
print(____[["params.model_name", "metrics.mape"]])