Table 5.

Precision of clustering algorithms with different feature selection methods.

	All Features	ReliefF	RFE	LS	MCFS	DGUFS	UFSOL
NC	0.619 (0.018)	0.589 (0.009)	0.573 (0.008)	0.627 (0.010)	0.633 (0.012)	0.633 (0.009)	0.633 (0.010)
SC	0.554 (0.019)	0.529 (0.011)	0.509 (0.008)	0.563 (0.010)	0.581 (0.013)	0.592 (0.008)	0.600 (0.009)
RBF-KC	0.490 (0.018)	0.483 (0.009)	0.467 (0.002)	0.511 (0.009)	0.520 (0.009)	0.531 (0.012)	0.540 (0.007)
KKM-KC	0.587 (0.019)	0.570 (0.010)	0.537 (0.002)	0.601 (0.008)	0.629 (0.008)	0.658 (0.012)	0.660 (0.008)
DBSCAN	0.629 (0.019)	0.600 (0.010)	0.564 (0.005)	0.633 (0.009)	0.654 (0.012)	0.689 (0.09)	0.689 (0.009)