Random forest for classification

The Random Forest algorithm creates an ensemble model of decision trees. Each tree is trained on a randomly selected subset of the training data.

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:

• RF_CLASSIFIER
• PREDICT_RF_CLASSIFIER
• PREDICT_RF_CLASSIFIER_CLASSES
• GET_MODEL_SUMMARY

For a complete example of how to use the Random Forest algorithm in Vertica, see Classifying data using random forest.