The Importance of Analyzing Model Assumptions in Machine Learning

With this summary, we can see important values such as R2, the F-statistic, and many others. You can also analyze a model using a graphical diagnostic such as plotting the residuals against the fitted/predicted values. Above is the fitted versus residual plot for our weight-height dataset, using height as the predictor. For the most part, this plot is random. However, as fitted values increase, so does the range of residuals.