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What is Notes 03 about?

The document discusses supervised learning in machine learning, focusing on concepts such as features, labels, training and test data, and various loss functions used to evaluate model performance. It introduces the k-Nearest Neighbor (kNN) algorithm, explaining its principles, characteristics, and practical considerations, including the choice of k and distance metrics. Additionally, it covers classification performance evaluation metrics like accuracy, confusion matrix, sensitivity, specificity, and the t

Author

fibeb77393

Language

EN