Mastering Machine Learning with scikit-learn - Second Edition

Evaluating the fitness of the model with a cost function

Regression lines produced by several sets of parameter values are plotted in the following figure. How can we assess which parameters produced the best-fitting regression line?

A cost function, also called a loss function, is used to define and measure the error of a model. The differences between the prices predicted by the model and the observed prices of the pizzas in the training set are called residuals, or training errors. Later, we will evaluate the model on a separate set of test data. The differences between the predicted and observed values in the test data are called prediction ...