MACHINE LEARNING

Detailed explanation-1: -Q5. Which of the following evaluation metrics can be used to evaluate a model while modeling a continuous output variable? Since linear regression gives output as continuous values, so in such cases, we use mean squared error or r-squared metric to evaluate the model performance.

Detailed explanation-2: -Evaluate Quality Using Model Metrics To evaluate your model’s quality, commonly-used metrics are: loss. accuracy. precision & recall.

Detailed explanation-3: -Accuracy, confusion matrix, log-loss, and AUC-ROC are some of the most popular metrics. Precision-recall is a widely used metrics for classification problems.