EURASIP Journal on Information Security

Table 4 Accuracy on the SPAM_BASE 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	2	60		16	300	0.918	1	0.837	0.000
	4	33		16	297	0.866	2	0.782	0.000
h-FPF	2	60		16	300	0.913	1	0.834	−0.003
	4	33		8	297	0.865	2	0.775	−0.007
RSM			0.2	16	300	0.909	1	0.837	0.000
			0.2	16	300	0.909	2	0.736	−0.046
RF				8	300	0.923	1	0.766	−0.071
				4	300	0.902	2	0.449	−0.333
RT	3			8	300	0.715	1	0.433	−0.422
	3			8	300	0.715	2	0.201	−0.655

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