Boosting Learner Loop Start – KNIME Community Hub

Node / LoopStart

Boosting Learner Loop Start

Analytics Mining Ensemble Learning

Together with the corresponding loop end node a boosting loop can be constructed. It repeatedly trains simple models and weights them according to their classification error. The algorithm used is AdaBoost.SAMME, i.e. is can also cope with multi-class problems. The first output contains the re- and over-sampled dataset, rows that have been predicted wrong are contained more often than correctly predicted rows.

Node details

Ports Options Views

Input ports

Type: Table

Input

Any input data with nominal class labels

Output ports

Type: Table

Training data

Possibly re-sampled training data, must be connected to the learner node inside the loop
Type: Table

Output

Unaltered input data, must be connected to the predictor node inside the loop

Extension

The Boosting Learner Loop Start node is part of this extension:

Go to item