I am writing a section on software comparison and I wish to describe KNIME accurately, so I am turning to the community for help. I am a complete novice in KNIME. I wish to build the simplest k-fold cross-validation workflow possible with the tool.
Would this be a correct sequence of components for 10-fold cross-validation with random forest? The aim is to observe confusion matrix and ROC curve of the evaluation results.
Also, is it perhaps possible to observe misclassifications from the confusion matrix in a visualization? I.e. select misclassifications and see them exposed in the scatter plot?
Any suggestions or comments much appreciated!