@inproceedings{minka2000bayesian,
author = {Minka, Tom},
title = {Bayesian Model Selection},
year = {2000},
month = {September},
abstract = {Bayesian model selection uses the rules of probability theory to select among different hypotheses. It is completely analogous to Bayesian classification. It automatically encodes a preference for simpler, more constrained models, as illustrated at right. Simple models, e.g. linear regression, only fit a small fraction of data sets. But they assign correspondingly higher probability to those data sets. Flexible models spread themselves out more thinly.},
url = {http://approjects.co.za/?big=en-us/research/publication/bayesian-model-selection/},
}