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 🔴 Subscribe for more videos on Machine Learning and Python. 👍 Smash that like button,
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