Area under a curve.

[mlauber71]

@Gimli question is what do you want to measure. the nodes mentioned would have a prediction (score) that typically rund between 0 and 1 and a (binary) variable of 1 and 0 (true/false) that would be the ground truth about what your model tried to predict (taken from the test or validation data). You can read more about that here:

H2O.ai AutoML in KNIME for classification problems

H2O.ai Automl - a powerful auto-machine-learning framework wrapped with KNIME It features various models like Random Forest or XGBoost along with Deep Learning. It has wrappers for R and Python but also could be used from KNIME. The results will be written to a folder and the models will be stored in MOJO format to be used in KNIME (as well as on a Big Data cluster via Sparkling Water). One major parameter to set is the running time the model has to test various models and do some hyperparam…

If you have other constellations or you have a regression model other statistics / graphics would be needed.