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  2. Build from Scratch: Classification and Regression guide
  3. Predictive Modeling: Train your own machine-learning model & make predictions

Evaluating trained models

Compare trained models and understand how they generate predictions

In this article, you will compare different successfully trained models.

1. Navigate to the model leaderboard

Navigate your way to the model leaderboard by clicking on Models in the left navigation.

Note: Only the successfully trained model are listed on the model leaderboard. If you can’t see some models that you selected for training on the leaderboard, you can go to the model list tab to check on the status of all models.

 Model Leaderboard

2. View the highest-ranking models on different criteria

On the summary cards, you can see the models that rank 1st in each of the following criteria:

  • Best prediction quality

  • Shortest prediction time

  • Shortest training time

While on these summary cards, you then can:

  • Check for the deployment status

  • Deploy the model

  • Go to the individual model page

Model leaderboard summary cards

3. Compare models on the model ranking table

By default, on the model ranking table, the models are sorted in descending order of prediction quality. You can use the “Ranking based on” dropdown tab to change the ranking criteria to one of the following:

  • Prediction time

  • Training time

You can also click on the column headers to sort the models accordingly. In particular, by clicking on the column header “Prediction quality”, the models will be sorted in descending order based on their prediction qualities. By clicking the “Prediction time” and “Training time” headers, the models are sorted in ascending order of the corresponding time.

Model leaderboard

Tip: To see the metrics used for prediction quality, check out this article

On the ranking table, you can:

  • Check for the deployment status

  • Deploy the model

  • Go to the individual model page

4. Go to the individual model’s performance page

By clicking on the model name on the summary cards or the ranking table, you will land at the corresponding model's individual page, at the model summary tab.

On this page, you can:

  • View the summary card of the model’s performance on the latest test portion, under the “Insights” section

  • Click on the performance summary card to view the detailed report on different test portions, showing the charts and metrics corresponding to the machine-learning model

  • Alternatively, click on the “Insights” tab and the “Performance” sub-tab to have the same detailed view of the model’s performance.

Model performance viewViewing detailed performance from the summary cards

Model performance viewViewing detailed performance using the table view and tabs

Tip: To see how to evaluate regression model performance, check out this article.