Residual plots

Residual plots are graphs used to assess the accuracy of a predictive model. They display the differences between observed data points and the model's predicted values, called residuals. By plotting these residuals against predicted values or input variables, we can identify patterns or inconsistencies, such as non-linearity or unequal spread, which indicate potential issues with the model. A good model will have residuals randomly scattered around zero without any clear pattern, suggesting it fits the data well. Residual plots are essential tools for diagnosing and improving statistical or machine learning models.