CA.knwf (3.5 MB)
Sorry for the noob question, im new to Knime and totally cant figure out how. I have tried to use 3 models (KNN, decision tree and random forest) to predict loan status, and all of them are predicting more “1” than “0”, especially random forest, which is almost only predicting “1”.
I have tried to use stratified sampling and SMOTE but I guess i did something wrong they were not working.
I have also tried equal size sampling, prediction is less biased but accuracy drops from already low 60% something to 40% something.
Would appreciate any help on how to fix the biased prediction while maintaining accuracy (or maybe improve accuracy?), thank you!