Decision Tree Predicting Only One Outcome?

[mlauber71]

Question is what you mean by optimized for a given model. If you want to finde the best cutoff point, I have built a MetaNode that would evaluate a given model (solution - the truth: 1/0 and submission (score 0-1) and recommend a best cut-off point using two statistics:

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…

Also, H2O.ai Automl would come back with a best cutoff based on F1 score. But please keep in mind: in the end, you will have to make a business decision what score represents a correct hit.