Table 8.

Classification results of algorithms using leave drug combinations out on HT29

HT29	AUC	F1 score	F1 score*	Recall			Precision			Rank	Rank*
				Additive	Antagonism	Synergy	Additive	Antagonism	Synergy
SVM	0.5963	0.3566	0.1974	0.8117	0.1560	0.1381	0.6231	0.2758	0.3253	5.8	5.8
KNN	0.5574	0.3429	0.1641	0.8660	0.1154	0.1147	0.6306	0.3209	0.2517	6.3	8.0
XGB	0.6046	0.3559	0.1864	0.8737	0.1145	0.1378	0.6258	0.3090	0.4061	4.7	5.8
MLP	0.5989	0.3448	0.1826	0.8462	0.1190	0.1418	0.6220	0.3028	0.3072	6.1	6.3
DT	0.5067	0.3710	0.2527	0.6153	0.2574	0.2611	0.6238	0.2332	0.2597	6.1	6.0
GDBT	0.6073	0.3655	0.2009	0.8641	0.1424	0.1435	0.6374	0.3020	0.3738	3.7	4.5
RF	0.6121	0.3451	0.1884	0.8180	0.1137	0.1763	0.6279	0.2123	0.3260	5.7	6.1
Single-layer Network	0.5284	0.2031	0.2482	0.3675	0.1728	0.4745	0.3439	0.1454	0.2572	8.1	6.0
DeepSynergy	0.5118	0.2526	0.0576	0.8470	0.1346	0.0000	0.6155	0.1007	0.0000	9.1	10.1
MatchMaker	0.5777	0.3124	0.3177	0.3759	0.5420	0.3039	0.5733	0.2605	0.2483	7.1	5.0
EDST	0.6129	0.4159	0.3283	0.5945	0.3464	0.3453	0.6499	0.3504	0.2746	2.8	2.1

The symbol [bold] indicates the highest value in the same evaluation indicator