H2O AutoML for Regression workflow "improvement"

[leinmi]

Hello,

I am testing this workflow:

H2O AutoML for Regression – knime

I would like to know if it is possible to add some sort of metrics or graph which shows which variable in input data has biggest impact to prediction?

Regards,
Mika

[mlauber71]

@leinmi that is a very good idea since H2O.ai does provide such a list, You can access that when using the models thru R or Python. I wrote an article how to do that with KNIME as a wrapper:

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…

H2O.ai AutoML in KNIME for regression 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…

[leinmi]

Thank you! I will look at these