What is the difference between classification and regression accuracy?

What is the difference between classification and regression accuracy?

Classification accuracy measures the percentage of correct predictions in a classification task, while regression accuracy evaluates how close predicted values are to actual values.

Can you give me an example of each?

Sure! In classification, if you predict whether emails are spam or not, accuracy is the ratio of correctly identified emails. In regression, predicting house prices based on features like size and location, accuracy is measured by how close the predicted prices are to the actual prices.

How do I improve accuracy in classification tasks?

You can improve classification accuracy by using better features, tuning hyperparameters, or employing ensemble methods like Random Forests.

What metrics can I use to evaluate regression models?

Common metrics for regression evaluation include Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared.