Evaluate Your Model's Performance in Amazon SageMaker Canvas - Amazon SageMaker

Evaluate Your Model's Performance in Amazon SageMaker Canvas

After you’ve built your model, you can evaluate how well your model performed on your data before using it to make predictions. You can use information, such as the model’s accuracy when predicting labels and advanced metrics, to determine whether your model can make sufficiently accurate predictions for your data.

On the Analyze page for your model, Amazon SageMaker Canvas provides the following three tabs:

  • Overview – Gives you a general overview of the model’s performance, depending on the model type.

  • Scoring – Shows visualizations that you can use to get more insights into your model's performance beyond the overall accuracy metrics.

  • Advanced metrics – Contains your model’s scores for advanced metrics and additional information that can give you a deeper understanding of your model's performance. You can also view information such as the column impacts.

The section Evaluate your model's performance describes how to view and interpret your model’s Overview and Scoring tabs. The section Use advanced metrics in your analyses contains more detailed information about the Advanced metrics used to quantify your model’s accuracy.

You can also view more advanced information for specific model candidates, which are all of the model iterations that Canvas runs through while building your model. Based on the advanced metrics for a given model candidate, you can select a different candidate to be the default, or the version that is used for making predictions and deploying. For each model candidate, you can view the Advanced metrics information to help you decide which model candidate you’d like to select as the default. You can view this information by selecting the model candidate from the Model leaderboard. For more information, see .

Canvas also provides the option to download a Jupyter notebook so that you can view and run the code used to build your model. This is useful if you’d like to make adjustments to the code or learn more about how your model was built. For more information, see Download a model notebook.