Machine Learning | ROC and AUC Curves

ROC and AUC curves are important evaluation metrics for calculating the performance of any classification model. These definitions and jargons are pretty common in the Machine learning community and are encountered by each one of us when we start to learn about classification models. However, most of the times they are not completely understood or rather misunderstood and their real essence cannot be utilized. Under the hood, these are very simple calculation parameters which just needs a little demystification. We will solve a problem-based on ROC and AUC to understand this. #MachineLearning #ROC #AUC
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[@RanjiRaj18]

For notes👉 github.com/ranjiGT/ML-latex-amendments

[@srtalukdar]

You made my day Ranji Raj! This is the best explanation on this topic.

[@VijayMauryavm]

Thanks I got clarity on Area under curve calculation

[@mpushpak8787]

Superb Vedic
Your explanation is very nice
Thanku

[@ajayakumarsatapathy6811]

from which book we can get all machine learning mathematical derivation and example of solving through paper and pen. suggest Indian author please.

[@senthilmuruganms4473]

we find the best model by score but how to find threshold point to classify using sklearn metrics