Retraining Random Forest Model

We launched an upgraded Random Forest Model training algorithm in early February 2025 with improved classification performance and computational efficiency. We no longer support classification using models trained prior to this date. However, you can retrain your model for the new RFM algorithm with the exact dataset used to train your original model. This “Retrain” feature is available for models trained before February 5, 2025.

How to Retrain a Random Forest Model

1. Go to the Project - Open the project containing the model you want to retrain.
2. Navigate to the Random Forest Model - Locate the trained Random Forest Model from the Training Results section.
3. Click the "Retrain" button.

Note:

• You cannot change the parameters when retraining the model.
• You can retrain the model once. The retrain button will be disabled after the model has been retrained.
• You cannot retrain a shared Random Forest model that originated from another project.

You can see the retrain history on the Model Detail Page.