This node uses the spark.ml linear regression implementation to train a linear regression model in Spark, supporting different regularization options. The target column must be numeric, 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 2.4.