From: Accurate molecular classification of cancer using simple rules
Methods (feature selection + classification)a | #Selected genes | #Correctly classified samples (accuracy) | Rule-based classifier |
---|---|---|---|
depended degree + decision rules [this work] | 1 | 31 (91.18%) | yes |
 | 2 | 34 (100%) |  |
t-test, attribute reduction + decision rules [7] | 1 | 31 (91.18%) | yes |
attribute reduction + k-NNs [9] | 2 | 33 (97.06%) | no |
rough sets, GAs + k-NNs [10] | 9 | 31 (91.18%) | no |
EPs [6] | 1 | 31 (91.18%) | yes |
discretization + decision trees [11]b | unknownc | 31 (91.18%) | yes |
CBF + decision trees [24] | 1 | 31 (91.18%) | yes |
TSP [14] | 2 | 31 (91.18%) | yes |
RCBT [13] | 10-40 | 31 (91.18%) | yes |
neighborhood analysis + weighted voting [2] | 50 | 29 (85.29%) | no |
signal to noise ratios + PNNs [23] | 50 | 34 (100%) | no |
MAMA [25] | 132-549 | 34 (100%) | no |
PLS + LD or QDA [26] | 50-1500 | 28-33 (82.4%-97%) | no |
prediction strength + SVMs [27] | 25-1000 | 30-32 (88.2%-94.1%) | no |
8-30 | 34 (100%) | no |