Fisher's Criterion
Updated 2026-08-17
INTRODUCTION
English translation pending.
CORE DEFINITION
Associated with R. A. Fisher, the criterion commonly denotes the linear discriminant rule that selects the projection maximizing between-class variance while minimizing within-class variance, and by extension the randomization and analysis of variance ideas Fisher introduced. The key qualification is that the phrase has several meanings and must be read in context; the shared core is optimal separation under controlled error.
SCAFFOLDING EFFECT
Reduce cognitive load
- Best angle: ask which viewing direction separates the two groups most clearly from each other. - Variance split: maximize between-class differences while keeping every group internally tight. - Randomization guard: control bias and error by assigning experimental treatments strictly at random.
Anchor fast decisions
Two groups drawn from overlapping distributions look identical along most axes, and a badly chosen projection smears them together. Rotating the view onto the axis where between-class differences are large and within-class scatter is small pulls the groups apart, and randomization keeps assignment bias from manufacturing a fake separation.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Ronald_Fisherverified
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