Evaluating the classification model performance

Up to now, we have learned how to create classification models. Creating a machine learning classification model is not enough; as a business or data analyst, you also want to assess its performance so that you can deploy it in live projects.

scikit-learn offers various metrics, such as a confusion matrix, accuracy, precision, recall, and F1-score, to evaluate the performance of a model.