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I have attached the test process as XML which uses the Ripley dataset for example purpose. In a nutshell, I have optimized the threshold based on f-measure and then output the model performance for that "best threshold". Also, I have used the "ROC Curve to Example" operator from the Converters extension to generate 500 datapoints as an ExampleSet. I notice some discrepancy in the results which is intriguing. If someone could help reconcile it, it would be much appreciated.
- The best threshold is found out to be 0.642, which corresponds to a confusion matrix with TP=112, TN=104, FN=13, FP=21 with recall=TPR=89.6%, specificity=83.2%, FPR=1-specificity=16.8%, and F-measure=86.82%
- Now, the "ROC Curve to ExampleSet" output lists the different FPRs, TPRs, and confidence thresholds. I find that for TPR=89.6% and FPR=16.8%, the confidence (threshold) is listed as 0.356 which is puzzling. Also, for the confidence (threshold) of 0.643, TPR=66.4% and FPR=4.2%.
- Why do the values from steps 1 and 2 not match up?