During the Auto Model stage, we automatically train your models and rank them in a leaderboard, then you select what model you want to use. You can also see what features we’ve automatically created as part of the modeling and scoring process.
We automatically choose a performant model for you, but you can manually change what model you want to use from the dropdown.
You can also access Advanced settings at this stage.
The Leaderboard panel shows you information about the model you've selected, what models are available for you to select, and the ranking metric we've used to rank models in the leaderboard.
For any model you select, we show its score based on the ranking metric, how many features the model uses, how much better it has performed than a baseline model, and some highlights of the machine learning pipeline we've used to build the model.
The score differs based on the ranking metric you select. To learn more about specific ranking metrics, select the book icon in the header or Learn More from the Leaderboard panel.
The baseline model simulates a random guess.
The Features panel shows all the features we've used to create your machine learning models. We mark features we automatically engineered with an asterisk.