4 exercises found
Polynomial regression has the same trap as linear — if there is no pattern, fitting a curve just makes your mistakes fancier.
Only after your model passes the train/test check should you trust it to make real predictions.
Testing a model on the same data it learned from is like grading your own exam — you will always get 100%, but you have learned nothing.
Train the model on 80% of data, test on 20%, and compare R² scores — if both are similar, your model generalises well.