Table 7.

The correct classification rates (P_CCR), sensitivity (P_sens), and specificity (P_spec) percentages for the classification procedures based on models M_I(V, D) − M_IV (V, D) using hippocampal LDDMM metrics and volumes with optimum threshold values π_o = π_opt based on the cost function C₁(π_o, w₁, w₂) with w₁ = w₂ = 1 and w₁ = 1, w₂ = 3 (top); and with optimum threshold values π_o = π_opt based on the cost function C₂(π_o, η₁, η₂) with η₁ = η₂ = 0.5 and η₁ = .3, η₂ = 0.7 (bottom).

Using optimum πo based on cost function C1 (πo, w1, w2) with
	w1 = w2 = 1				w1 = 1, w2 = 3
	MI(V, D)*	MII(V, D)	MIII(V, D)	MIV(V, D)	MI(V, D)*	MII(V, D)	MIII(V, D)	MIV(V, D)
πopt	.64-.65	.66	.48-.58	.48	.64-.65	.66	.48-.54	.28-.33
PCCR	84%	84%	75%	84%	84%	84%	75%	80%
Psens	89%	83%	83%	83%	89%	83%	83%	89%
Pspec	81%	85%	69%	85%	81%	85%	69%	73%
Using optimum πo based on cost function C2(πo, η1, η2) with
	η1 = η2 = 0.5				η1 = .3, η2 = 0.7
	MI(V, D)*	MII(V, D)	MIII(V, D)	MIV(V, D)	MI(V, D)*	MII(V, D)	MIII(V, D)	MIV(V, D)
πopt	.64-.65	.66	.68-.72	.48	.64-.65	.66	.23	.20-.22
PCCR	84%	84%	80%	84%	84%	84%	70%	75%
Psens	89%	83%	61%	83%	89%	83%	100%	94%
Pspec	81%	85%	92%	85%	81%	85%	50%	61%

^*The model with the best classification performance is marked with an asterisk.