This lecture shows measures of performance for machine learning evaluation purposes.

⏲Outline⏲
00:00:00​ Introduction
00:04:10​ Confusion Matrix
00:07:19​ Precision
00:08:59​ Recall (Sensitivity)
00:10:30​ F1 Score
00:11:35​ Interpretations
00:15:42​ Precision/Recall Tradeoff
00:17:50​ Precision/Recall Adjustment
00:30:39​ ROC Curve
00:33:12​ Reading ROC Curves
00:33:32​ AUC metric
00:34:53​ Random Forest Classifier
00:37:27​ Outro

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#python #machine-learning