Classification Metrics Explained | Sensitivity, Precision, AUROC, & More
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In this video, I go through the different types of binary classification metrics. These include: accuracy, prevalence, confusion matrices, sensitivity (aka recall or true positive rate), specificity (aka true negative rate), precision (aka positive predictive value), F1 score, and the areas under the precision-recall curve and the receiver operating characteristic curve, that is: AUPRC and AUROC. We close with how to implement these using the scikit-learn package in Python, going through a Jupyter notebook.
Code can be found here: https://github.com/RichardOnData/YouT...
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