Gradient Boosted Trees are ensembles of Decision Trees. They iteratively train Decision Trees in order to minimize a loss function. This node uses the spark.ml Gradient Boosted Trees implementation to train a regression model in Spark. The target column must be numerical, whereas the feature columns can be either nominal or numerical.
Use the Spark Predictor (Regression) node to apply the learned model to unseen data.
Please refer to the Spark documentation for a full description of the underlying algorithm.
This node requires at least Apache Spark 2.0.