Evaluating Logistic Regression Models
Explore how to evaluate logistic regression models using multiple metrics beyond accuracy, including precision, recall, F1-score, and support. Understand concepts like true positive, false positive, and how imbalanced classes affect model performance. Gain insights on applying these evaluations to improve predictive classification models.
We'll cover the following...
We'll cover the following...
Evaluating classification models
Just like there were many ways to evaluate linear regression models, there are many ways to evaluate the performance of classification models. Accuracy is one of the techniques. But it is not a sufficient metric alone. Why?
Think about a scenario where our model predicts a rare disease that is present only in 0.01% of the data. If our model always ...