How to compare different models

[mlauber71]

OK, there is the Binary Classification Inspector that would give you an idea about the model.

Binary Classification Inspector Example

I created two Meta nodes for binary and regression models that would run a certain set of parameters and create some graphics (you would need some R packages). Input would just be a solution column with the truth either as 0/1 string or the number and a “submission” which is the score from 0-1.

You could collect the results from the statistic tables and see which model is best. But you might want to be careful since what is ‘best’ might depend on your business question and which cutoff you would come to use. The Meta node does suggest an optimal cutoff but you might want to include some costs (for misclassification).

The output is explained in more details 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…

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…

If you want to explore the possibilities of KNIME and machine learning further I have created a meta collection

Machine Learning Meta Collection (with KNIME) – mlauber71