AMATH 301 Lecture Notes - Lecture 11: Matlab, Root Mean Square, Dot Product
Document Summary
These notes reference files in canvas 1. % data fitting: we use a few kinds of ways to fit data in matlab, curve. Given x and y, we search for m. % and b in the equation y = mx + b. % to check our error, we are using the equation error_k = m * x_k + b. % where m*x_k + b = predicted value, and y_k is the actual value. % adjust our guesses using our error we calculate. % max error is given by taking the max of that equation. % average error is given by taking the sum of that equation squared, % and then dividing through by n. aka l1 error. % root mean square error is given by taking the square root of the entire. % we want to minimize e(m,b), and we do this with partial derivatives with.
