Discriminant function analysis: Difference between revisions

Revision as of 21:45, 13 December 2016

Revision as of 18:43, 6 March 2017

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*[[Maximum likelihood]]: Assigns x to the group that maximizes population (group) density.<ref name="har">Hardle, W., Simar, L. (2007). ''Applied Multivariate Statistical Analysis''. Springer Berlin Heidelberg. pp. 289-303.</ref>

*Bayes Discriminant Rule: Assigns x to the group that maximizes <math>\pi_i f_i(x)</math>, where ''π<mathsub>f_i(x)i</mathsub>'' represents the [[prior probability]] of that classification, and ''π<submath>if_i(x)</submath>'' represents the population density.<ref name="har"/>

*[[Linear Discriminant Analysis|Fisher’s linear discriminant rule]]: Maximizes the ratio between ''SS''_between and ''SS''_within, and finds a linear combination of the predictors to predict group.<ref name="har"/>