# Decision Tree Predicting Only One Outcome? **URL:** \ **Category:** KNIME Analytics Platform\ **Created:** [January 31, 2019, 9:49pm UTC](https://forum.knime.com/t/decision-tree-predicting-only-one-outcome/13348 "2019-01-31T21:49:29Z")\ **Posts on this page:** 1\ **Showing post:** 6
**Author:** ![mlauber71](https://forum-cdn.knime.com/user_avatar/forum.knime.com/mlauber71/32/73590_2.png) [@mlauber71](https://forum.knime.com/u/mlauber71)\ **Post date:** [August 9, 2020, 9:35am UTC](https://forum.knime.com/t/decision-tree-predicting-only-one-outcome/13348/6 "2020-08-09T09:35:10Z")
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](https://forum.knime.com/t/h2o-ai-automl-in-knime-for-classification-problems/20923): > > 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… ![image](https://forum-cdn.knime.com/uploads/default/original/3X/b/5/b52835b082a5b0eea0b6296fad63b46ae35d41af.png) 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. --- _[View the full topic](https://forum.knime.com/t/decision-tree-predicting-only-one-outcome/13348)._