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).

Deze oefening maakt deel uit van de cursus

Designing Forecasting Pipelines for Production

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Oefeninstructies

Search MLflow runs by the experiment_name.
Get the single best-performing model from all_results based on metrics.mape.
Print the subset of best_mape_model.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

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"]])

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