Table 9.

The correct classification rates (P_CCR), sensitivity (P_sens), and specificity (P_spec) percentages for the classification procedures based on models M_I (D^APC) − M_III (D^APC) using APC in metric distances 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 (DAPC)*	MII (DAPC)*	MIII (DAPC)	MI (DAPC)	MII (DAPC)	MIII (DAPC)
πopt	.45	.45-.46	.41	.42	.45-.46	.36
PCCR	66%	66%	66%	61%	66%	64%
Psens	61%	61%	56%	67%	61%	78%
Pspec	69%	69%	73%	58%	69%	54%
Using optimum πo based on cost function C2(πo, η1, η2) with
	η1 = η2 = 0.5			η1 = .3, η2 = 0.7
	MI (DAPC)	MII (DAPC)	MIII (DAPC)*	MI (DAPC)	MII (DAPC)	MIII (DAPC)
πopt	.45	.45-.46	.32	.37	.35-.36	.29
PCCR	66%	66%	64%	52%	55%	59%
Psens	61%	61%	89%	100%	100%	100%
Pspec	69%	69%	46%	19%	23%	31%

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