ML 4: A Learning Curve Fitted Early Promises More Than More Data Delivers
Disclosure: this post was written with the assistance of an AI system (Claude), which wrote the analysis code, ran the experiments and drafted the text. The topic, the constraints, the data choices and the final review are the author’s. On a simulated task whose Bayes error is 0.268, with training sets grown to 25,600 rows, the two-parameter power law a n^-b fitted to the smaller sizes predicted too low an error in all 9 fits, and in 4 of them predicted an error below the Bayes error - 0....