XGBoost Predictor

Applies a classification XGBoost model to predict data.


Change prediction column name
Select if you want to specify a custom name for the prediction column. Otherwise a default column name based on the target column is used.
Prediction column name
The name of the prediction column.
Append individual class probabilities
Check if the output table should also contain for each row the probabilities of it belonging to each class.
Suffix for individual class probabilities
The suffix to append to the column names of the probability columns. This can be useful to distinguish probabilities predicted from different models.
Handle unknown categorical features as missing features
If checked, unknown categorical features are treated as if they were missing values. Otherwise the node will just fail. A value is considered to be unknown if it was not among the values encountered during model training in the Learner node.
Batch size
Controls the number of rows to predict together. Larger values tend to improve performance while also increasing the memory demand of the node.

Input Ports

The XGBoost model.
The data to predict.

Output Ports

The data with the appended prediction.


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