Spark Gradient Boosted Trees Learner (Regression)

Node / Learner

Spark Gradient Boosted Trees Learner (Regression)

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.

Node details

Ports Options Views

Input ports

Type: Spark Data

Input data

Input Spark DataFrame with training data.

Output ports

Type: Table

Feature importance measures

Table with estimates of the importance of each feature. The features are listed in order of decreasing importance and are normalized to sum up to 1.
Type: Spark ML Model

Spark ML Gradient Boosted Trees model (regression)

Spark ML Gradient Boosted Trees model (regression)

Extension

The Spark Gradient Boosted Trees Learner (Regression) node is part of this extension:

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