A Quantitative Occam's Razor

Extending Occam's Razor

Occam's Razor states that, all other things being equal, the simpler of two possible hypotheses is to be preferred. A quanti ed version of Occam's Razor has been proven for the PAC model of learning, giving sample-complexity bounds for learning using what Blumer et al. call an Occam algorithm [1]. We prove an analog of this result for Haussler's more general learning model, which encompasses le...

Papers Merit Goods, Consumer Sovereignty, and Efficiency: a Suggested Application of Occam's Razor

Conditions for Occam's Razor Applicability and Noise Elimination

The Occam's razor principle suggests that among all the correct hypotheses, the simplest hypothesis is the one which best captures the structure of the problem domain and has the highest prediction accuracy when classifying new instances. This principle is implicitly used also for dealing with noise, in order to avoid overrtting a noisy training set by rule truncation or by pruning of decision ...

Title: Intercepting Free Falling Objects: Better Use Occam's Razor than Internalize Newton's Law

Occam's Razor & The Nature of Scientific Theories

he early 14th century philosopher William of Occam (Sahakian 1968, p. 116) is credited by historians for proposing that, in interpreting scientific data, the simplest explanation consistent with all the known facts is preferred as a working hypothesis over more complicated ones. In other words, scientific explanations should be pared down (as if using a knife to cut away unnecessary "fat" from ...