yes, the output is continuous. So I used a threshold to get binary labels. If prediction < threshold, then class is 0 else 1. I use this binary label to then compute the accuracy. Even with this binary transformation, the accuracy with decision tree model is low compared to LR or SVM (for the specific dataset I used).
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