I'm starting to work with decision trees, and to begin I looked into the decision tree workflow already provided in the Alteryx workflow samples (Sample Workflow -> Predictive Analytics -> 6 Decision Tree).
After running the workflow and looking into the Browse Tool for the I Output, I run into an issue understanding the calculations for the Precision and Recall (under the summary tab).
Combining the numbers from the Misclassifications tab and the definitions of Precision and Recall (according to wiki), I would expect:
Precision = True Positive / (True Positive + False Positive) = 123 / (123+26) = 0.8255 = 82.55% (different from the 75.7% in the Summary Tab)
Recall = True Positive / (True Positive + False Negative) = 123 / (123+70) = 0.6373 = 63.73 % (different from the 53.6% in the Summary Tab)
Is there something I'm misunderstanding from these calculations? - perhaps some correctional factors.