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Interpret the Leaderboard

The Leaderboard provides useful summary information for each model built in a project and ranks them based on the chosen optimization metric—meaning the best performing models are at the top. From the Leaderboard, you can also access a variety of insight tabs to further fine-tune and evaluate your models.

To access the Leaderboard, click Models > Leaderboard at the top of the page.

Takeaways

This tutorial explains:

  • How to read the following model summary information on the Leadboard:
    • Performance metrics
    • Model badges, icons, and indicators
    • Recommended models
    • Feature list and sample size
  • How to filter the Leaderboard

Compare performance metrics

Models are ranked by the optimization metric chosen prior to model building, which is displayed at the top. The Leaderboard displays the model's Validation, Cross Validation, and Holdout (if unlocked) scores.

Performance metrics

To change the optimization metric used for ranking, click the Metric dropdown and select a new metric.

Performance metrics

Understand model icons

The Leaderboard provides a wealth of information for each model built in a project using various badges, tags, and indicators. The badge to the left of the model name indicates the type, and the text below describes model type and version, or whether it uses unaltered open source code.

Model badges

The tags and indicators along the bottom provide quick model identifying and scoring information.

Model tags and indicators

The model at the top of the list features a Recommended for deployment tag, meaning DataRobot recommends and prepares the model for deployment based on its accuracy and complexity.

Recommended model

Before selecting the recommended model, compare it against other models on the leaderboard using the model comparison tools to make sure it's the best model for your use case.

Starred models

Starring models on the Leaderboard allows you to quickly find certain models later on.

  1. Hover over the model you would like to star.

    Hover over favorite model

  2. Click the star icon. When the star is filled in, that means you've successfully marked this model as a favorite.

    Favorite icon

Read feature list and sample size

The Feature List & Sample Size column displays the feature list and sample size used to build the model and allows you to retrain the model using different parameters.

Feature list and sample size

Filter the Leaderboard

If you're looking for a specific model or model criteria, you can filter the Leaderboard to narrow down the results.

By optimiziation metric

To sort by Validation, Cross Validation, or Holdout scores, click the column header. When the header is blue, the Leaderboard lists models from most accurate to least accurate for the selected partition.

By starred models

To view all starred models, click Filter Models and select Starred Models. The Leaderboard updates to only display models that have been starred.

Filter by favorite models

By sample size and feature list

You can also filter Leaderboard models by the feature list and sample size used to build them.

  1. Click the Feature List & Sample Size column header.
  2. Select the feature list and sample size parameters of the models you would like the Leaderboard to display.

    Filter by favorite models

Learn more

Documentation:


Updated June 8, 2022
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