Training an algorithm on a very few number of data points (such as 1, 2 or 3) will easily have 0 errors because we can always find a quadratic curve that touches exactly those number of points. Hence:
- As the training set gets larger, the error for a quadratic function increases.
- The error value will plateau out after a certain m, or training set size.
