Build Accurate Models Using Random Forest Algorithms (Pilot)

Einstein Discovery now adds a fourth type of model that is based on a modeling algorithm known as random forest. Einstein Discovery uses this supervised learning algorithm to create highly accurate models via multiple decision trees, randomization, and other optimization techniques. You can compare a random forest model with other types of models to determine whether this algorithm provides better accuracy for your story.
Note

Note

We provide random forest model functionality to selected customers through a pilot program that requires agreement to specific terms and conditions. To be nominated to participate in the program, contact Salesforce. Pilot programs are subject to change, and we can’t guarantee acceptance. Random forest models are not generally available unless or until Salesforce announces its general availability in documentation or in press releases or public statements. We can’t guarantee general availability within any particular time frame or at all. Make your purchase decisions only based on generally available products and features. You can provide feedback and suggestions for random forest models in the applicable IdeaExchange group in the Trailblazer Community.

Where: This change applies to Einstein Analytics in Lightning Experience and Salesforce Classic. Einstein Analytics is available in Developer Edition and for an extra cost in Enterprise, Performance, and Unlimited editions.

How: In story setup, click the Algorithm list and select Random Forest (Pilot).

Model Versioning

After creating the story, go to Model Metrics and compare the accuracy of this model with models created using other algorithms.

Note

Note

For the pilot, random forest models have limited interpretability and cannot be deployed.