Evaluating Classification Models - Evaluation Metrics Theory RENEW Later Evaluation metrics help us to evaluate, compare and finetune our machine learning algorithms. Whether you continue in the world of coding, or simply want to engage in conversations about machine learning, your understanding of these metrics will underpin your ability:r to make good decisions. Directions: Match the descriptions to the metric names. A. The proportion of all observations that Y Recall were correctly classified. v Precision B. The proportion of positive predictions that were correctly classified. 7 Accuracy C. The proportion of positive cases that were correctly classified. Y El Score D. An average that balances both precision and accuracy. l} E. An average that balances both precision and recall