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Lecture
Quantifying Performance: Misclassification and F-Measure
Description
This lecture covers the estimation of data points from sampling, cross-validation techniques, quantifying performance through true positives, false negatives, and false positives, determining the optimal model, detecting overfitting, and the sensitivity of performance to various factors in machine learning.
Official source
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