Multiconstrained gene clustering based on generalized projections

BMC Bioinformatics

Table 6 Five-fold cross-validation of the NMI values on SGD clusters

Datasets	POCS	k-medoids[10]	ICM[12]	FCM[13]
(a) K = 10
alpha	0.438 ± 0.008	0.383 ± 0.002	0.404 ± 0.002	0.408 ± 0.003
cdc15	0.462 ± 0.001	0.389 ± 0.004	0.422 ± 0.003	0.429 ± 0.004
cdc28	0.428 ± 0.005	0.387 ± 0.001	0.400 ± 0.002	0.411 ± 0.004
elu	0.432 ± 0.006	0.410 ± 0.004	0.411 ± 0.003	0.412 ± 0.004
Hughes	0.467 ± 0.004	0.414 ± 0.009	0.434 ± 0.003	0.439 ± 0.003
(b) K = 15
alpha	0.533 ± 0.003	0.471 ± 0.006	0.507 ± 0.004	0.517 ± 0.004
cdc15	0.572 ± 0.002	0.507 ± 0.005	0.528 ± 0.005	0.540 ± 0.003
cdc28	0.552 ± 0.001	0.488 ± 0.004	0.524 ± 0.005	0.543 ± 0.003
elu	0.536 ± 0.008	0.466 ± 0.004	0.514 ± 0.003	0.525 ± 0.003
Hughes	0.566 ± 0.001	0.513 ± 0.007	0.549 ± 0.003	0.546 ± 0.005
(c) K = 20
alpha	0.607 ± 0.003	0.551 ± 0.003	0.579 ± 0.004	0.583 ± 0.004
cdc15	0.613 ± 0.001	0.543 ± 0.005	0.580 ± 0.003	0.587 ± 0.004
cdc28	0.598 ± 0.002	0.551 ± 0.003	0.587 ± 0.004	0.586 ± 0.005
elu	0.593 ± 0.001	0.539 ± 0.006	0.567 ± 0.004	0.564 ± 0.003
Hughes	0.638 ± 0.004	0.576 ± 0.003	0.586 ± 0.005	0.591 ± 0.003
(d) K = 25
alpha	0.649 ± 0.002	0.586 ± 0.004	0.636 ± 0.004	0.634 ± 0.006
cdc15	0.648 ± 0.006	0.594 ± 0.005	0.621 ± 0.004	0.620 ± 0.005
cdc28	0.661 ± 0.003	0.607 ± 0.005	0.630 ± 0.005	0.637 ± 0.006
elu	0.637 ± 0.004	0.607 ± 0.008	0.619 ± 0.006	0.621 ± 0.005
Hughes	0.667 ± 0.003	0.617 ± 0.009	0.637 ± 0.004	0.646 ± 0.005

ISSN: 1471-2105