Random forest for regression

The Random Forest for regression algorithm creates an ensemble model of regression trees. Each tree is trained on a randomly selected subset of the training data. The algorithm predicts the value that is the mean prediction of the individual trees.

You can use the following functions to train the Random Forest model, and use the model to make predictions on a set of test data:

• GET_MODEL_SUMMARY
• PREDICT_RF_REGRESSOR
• RF_REGRESSOR

For a complete example of how to use the Random Forest for regression algorithm in Vertica, see Building a random forest regression model.