Utilizing maximal frequent itemsets and social network analysis for HIV data analysis

Table 9 Schilling dataset—with feature selection

Methodology	Accuracy	Precision	Recall	F1	ROC-AUC
OE + RFE 100	0.911	0.71	0.702	0.675	0.943
OE + UNI 100	0.911	0.697	0.69	0.673	0.939
OE + PCA-100	0.886	0.581	0.631	0.614	0.920
OE + FI-BOTH + FI-CENTER + PCA-100	0.926	0.765	0.663	0.699	0.941
OE + FI-YES + FI-CENTER + PCA-100	0.931	0.797	0.665	0.715	0.951
OE + FI-NO + FI-CENTER + PCA-100	0.927	0.777	0.667	0.701	0.945
OE + FI-BOTH + RFE	0.911	0.718	0.667	0.66	0.941
OE + FI-BOTH + FI-CENTER + RFE	0.912	0.719	0.692	0.672	0.948
OE + FI-YES + RFE	0.909	0.703	0.695	0.674	0.944
OE + FI-YES + FI-CENTER + RFE	0.911	0.695	0.697	0.679	0.942
OE + FI-NO + RFE	0.913	0.72	0.676	0.668	0.939
OE + FI-NO + FI-CENTER + RFE	0.911	0.712	0.681	0.667	0.945
OE + FI-BOTH + uni	0.9	0.655	0.619	0.612	0.924
OE + FI-BOTH + FI-CENTER + uni	0.908	0.679	0.692	0.668	0.936
OE + FI-YES + uni	0.876	0.605	0.579	0.56	0.896
OE + FI-YES + FI-CENTER + uni	0.892	0.639	0.618	0.605	0.913
OE + FI-NO + uni	0.93	0.879	0.825	0.843	0.98
OE + FI-NO + FI-CENTER + uni	0.909	0.686	0.697	0.672	0.937
OE + FI-BOTH	0.908	0.706	0.683	0.66	0.94
OE + FI-NO	0.907	0.707	0.676	0.655	0.94
OE + FI-YES	0.9	0.712	0.706	0.677	0.941
OE + FI-BOTH + PCA-100	0.926	0.765	0.663	0.699	0.941
OE + FI-YES + PCA-100	0.931	0.797	0.665	0.715	0.951
OE + FI-NO + PCA-100	0.911	0.728	0.547	0.6	0.917

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