collect the results and sort them so you could easily see which models work best.
For Target 0/1 models Gini coefficient and Top Decile Lift should be your guide (the greater the better). For continous / numeric Targets you could use RMSE (0 is best) or Spearman if you just want a really good correlation between your score and the real values (but not necessary exactly predict them).
please download the complete DeepLearning (Keras, Tensorflow, H2O.ai) Workflow group:
https://kni.me/s/sl4rYEzjFPm7a99a
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
Download WorkflowDeploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.
Try NodePit Runner!Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to mail@nodepit.com, follow @NodePit on Twitter or botsin.space/@nodepit on Mastodon.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.