Data Science Interview Question: Creating ROC & Precision Recall Curves From Scratch

This is one of the popular data science interview questions which requires one to create the ROC and similar curves from scratch, i.e., no data on hand. For the purposes of this story, I will assume that readers are aware of the meaning and the calculations behind these metrics and what they represent and how are they interpreted. Therefore, I will focus on the implementation aspect of the same.

This ensures the following: The bads scores are higher than the goods scores for a substantially high cases The bads scores have proportionately higher number of positive scores and the goods scores have proportionately higher number of negative scores The bads scores are higher than the goods scores for a substantially high cases The bads scores have proportionately higher number of positive scores and the goods scores have proportionately higher number of negative scores We can of course...

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