Optimality Criteria
There are a variety of optimality criteria that can be used for controlling feature selection. The oldest are Mallows' Cp statistic and Akaike information criterion (AIC). These add variables if the t-statistic is bigger than .
Other criteria are Bayesian information criterion (BIC) which uses, minimum description length (MDL) which asymptotically uses, Bonnferroni / RIC which use, maximum dependency feature selection, and a variety of new criteria that are motivated by false discovery rate (FDR) which use something close to .
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Famous quotes containing the word criteria:
“We should have learnt by now that laws and court decisions can only point the way. They can establish criteria of right and wrong. And they can provide a basis for rooting out the evils of bigotry and racism. But they cannot wipe away centuries of oppression and injustice—however much we might desire it.”
—Hubert H. Humphrey (1911–1978)