EURASIP Journal on Information Security

Table 3 Accuracy on the BREAST_CANCER dataset (in boldface best results for each k)

From: Feature partitioning for robust tree ensembles and their certification in adversarial scenarios

Model	Parameters					Accuracy
	b	r	p	ml	\(\|{\mathcal {T}}\|\)	\(\phantom {\dot {i}\!}ACC_{A_{0}}\)	k	\(\phantom {\dot {i}\!}ACC_{A_{k}}\)	Δ f-FPF
f-FPF	3	42		8	300	0.939	1	0.912	0.000
	4	33		4	297	0.930	2	0.851	0.000
	5	27		8	300	0.930	3	0.816	0.000
h-FPF	3	42		8	300	0.939	1	0.912	0.000
	4	33		4	297	0.930	2	0.842	−0.009
	5	27		8	300	0.930	3	0.816	0.000
RSM			0.2	16	300	0.956	1	0.912	0.000
			0.2	16	300	0.956	2	0.833	−0.018
			0.2	16	300	0.956	3	0.658	−0.158
RF				4	300	0.930	1	0.877	−0.035
				8	300	0.947	2	0.842	−0.009
				4	300	0.930	3	0.614	−0.202
RT	1			4	300	0.923	1	0.562	−0.350
	1			4	300	0.923	2	0.505	−0.346
	1			4	300	0.923	3	0.454	−0.362

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