The contour plot is typically used to display how the error varies with varying coefficients that are being optimized in a machine learning algorithm, such as linear regression. If the linear regression coefficients are theta0 and theta1, and the error between the predicted value and the actual value is a Loss, then for a given Loss value, all the values of theta0 and theta1 form a contour. For different values of Loss, different contours are formed by varying the values of theta0 and theta1.
Contour plot
Getting ready
The data for Loss, theta0, theta1, and theta (optimal values of theta0 and theta1 that give the lowest error) are taken from one of the regression problems for plotting the contour plot. If theta0 and theta1...
