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Machine Learning Classification Metrics Explained (Confusion Matrix, Precision, Recall, F1, ROC AUC)
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YouTubeStudyPalz
Machine Learning Classification Metrics Explained (Confusion Matrix, Precision, Recall, F1, ROC AUC)
1. BINARY CLASSIFICATION – INTRODUCTION Definition: Binary Classification is a supervised learning task where output has only 2 classes. Examples: - Spam / Not Spam - Fraud / Not Fraud - Disease / No Disease Goal: Correctly classify data into one of two categories 2. CONFUSION MATRIX Definition: A table used to evaluate classification ...
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