This workflow demonstrates the functionality of the Binary Classification Inspector node. It produces a complex view made of four different charts in order to compare, optimize and select predictions of different binary classifiers.
It is possible to compare a number of binary classifier machine learning models predicting the same target on the same test data using performance metrics and ROC curves. Here three machine learning models are used: Bayesian, RandomForest, and XGBoost Tree.
By moving a threshold slider in the interactive view you can optimize a model by finding the best threshold given a performance metric of your choice.
It is possible to interactively select a given type of predictions (e.g. true positives) of one of the models and export them at the output of the node
Workflow
Binary Classification Inspector Example
Used extensions & nodes
Created with KNIME Analytics Platform version 4.1.0
- Go to item
- Go to item
- Go to item
- Go to item
- Go to item
- Go to item
Legal
By using or downloading the workflow, you agree to our terms and conditions.