An exact non-monotonic blend reference

A sign-quadrant classifier, in contrast, has joint accuracy $1/4$ for $1/2<\alpha <1$: it follows the distractor sign whenever signs disagree. At $\alpha =0.75$, a low trained accuracy can therefore coexist with full ideal label information.

The result concerns fresh independent uniform centers and exact observations. It is not automatically the Bayes accuracy for a finite empirical voice bank, quantized arithmetic, or additional input noise.