In Search of the Perfect Machine Learning Model

Probabilistic Performance and the Almost-Free Lunch

Principle Researcher: Dave Guggenheim, PhD

Introduction

In machine learning, the No Free Lunch Theorem (NFLT) indicates that every learning model performs equally well when their performance is averaged over all possible problems. Because of this equality, the NFLT is unequivocal — there is no single best algorithm for predictive analytics (Machine learning and it’s No Free Lunch Theorem | Brainfuel Blog).

At the same time, there …

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