klotz: false negatives* + machine learning* + confusion matrix* + false positives* + precision* + true negatives* + f1 score*

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  1. Learn about the importance of evaluating classification models and how to use the confusion matrix and ROC curves to assess model performance. This post covers the basics of both methods, their components, calculations, and how to visualize the results using Python.

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