"Estimating Learning Performance Using Hints"
Zehra Cataltepe and Yaser S. Abu-Mostafa
Connectionist Models Summer School, 1994

Abstract

Learning from hints is a learning mechanism that unifies learning from examples and learning from explicit rules. Performance of the learning system on different hints may be used to estimate the learning performance of the system on the function. We develop a formula that estimates learning performance, without using a validation error, but only errors on hints. We give the derivation and test examples for this specific formula.