Practice question · Multiple choice
A degree-19 polynomial through 20 noisy points passes through every one exactly, yet is a worse model than a straight line. Why does perfect fit indicate failure?
Hints
- Ask what the model would predict halfway between two data points.
- Fitting the data you have and predicting data you do not are different goals.
Show the answer
C. Because it has fitted the noise as well as the signal
Why
Fit quality on the training data is not model quality. A model with as many parameters as points always fits perfectly and has learned nothing generalisable.
Practise Interpolation and Curve Fitting
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