Discrimination Rules
- Maximum likelihood: Assigns x to the group that maximizes population (group) density.
- Bayes Discriminant Rule: Assigns x to the group that maximizes, where represents the prior probability of that classification, and πi represents the population density.
- Fisher’s linear discriminant rule: Maximizes the ratio between SSbetween and SSwithin, and finds a linear combination of the predictors to predict group.
Read more about this topic: Discriminant Function Analysis
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“Rules and particular inferences alike are justified by being brought into agreement with each other. A rule is amended if it yields an inference we are unwilling to accept; an inference is rejected if it violates a rule we are unwilling to amend. The process of justification is the delicate one of making mutual adjustments between rules and accepted inferences; and in the agreement achieved lies the only justification needed for either.”
—Nelson Goodman (b. 1906)