BibTeX
@MISC{Piël_no-free-lunchand,
author = {Nicholas Piël},
title = {No-Free-Lunch and the Minimum Description Length},
year = {}
}
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Abstract
The No-Free-Lunch theorem (NFL) states that no learning algorithm exists for the complete domain of problems that will outperform any other algorithm. Or in other words, every learning algorithm will perform equally well when averaged on the complete problem domain [3] The minimum description length (MDL) is a formalization of Occam’s Razor in which the best hypothesis
Citations
| 332 | Computer systems that learn - Weiss, Kulikowski - 1991 |
| 41 | A tutorial introduction to the minimum description length principle - Grunwald - 2004 |
| 22 | The supervised learning no-free-lunch theorems - WOLPERT - 2001 |
