PMML Gradient Boosted Trees Predictor

This Node Is Deprecated — This version of the node has been replaced with a new and improved version. The old version is kept for backwards-compatibility, but for all new workflows we suggest to use the version linked below.
Go to Suggested ReplacementPMML Gradient Boosted Trees Predictor

Applies classification from a Gradient Boosted Trees model that is provided in PMML format. Note that it is currently not possible to load models that were learned on a bit-, byte- or double-vector column and then written to PMML because PMML does not support vector columns. The implementation follows the algorithms described in "Greedy Function Approximation: A Gradient Boosting Machine" by Jerome H. Friedman (1999)". For more information you can also take a look at this .


Change prediction column name
Check this option if you want to use a custom name for the column containing the prediction
Prediction column name
Name of the output column containing the prediction.
Append overall prediction confidence
Appends a column that contains information on how the certain the model is about its prediction.
Append individual class probabilites
Appends for each possible class a column containing the probability that the given row is an element of this class
Suffix for probability column
Allows to add a suffix for the class probability columns.

Input Ports

Gradient Boosted Trees model in PMML format.
The data to predict.

Output Ports

The predicted data.


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