Table 12 Best learning schemes selected
From: A genetic algorithm based framework for software effort prediction
LS(DS=1) | F | % | LS(DS=2) | F | % | LS(DS=3) | F | % | LS(DS=4) | F | % |
|---|---|---|---|---|---|---|---|---|---|---|---|
7X5X6 | 203 | 33% | 6X2X14 | 188 | 30% | 2X5X1 | 322 | 50% | 7X1X6 | 207 | 32% |
1X1X11 | 154 | 25% | 7X3X14 | 158 | 25% | 2X5X6 | 69 | 11% | 6X5X3 | 114 | 18% |
6X2X4 | 115 | 19% | 7X1X14 | 118 | 19% | 2X4X1 | 61 | 9% | 6X1X3 | 113 | 18% |
1X5X11 | 46 | 8% | 1X5X14 | 66 | 11% | 7X4X6 | 59 | 9% | 7X5X6 | 76 | 12% |
1X1X2 | 44 | 7% | 7X3X11 | 62 | 10% | 1X4X6 | 57 | 9% | 5X2X1 | 61 | 10% |
6X3X8 | 11 | 2% | 6X4X14 | 16 | 3% | 2X5X2 | 51 | 8% | 2X2X1 | 59 | 9% |
Other | 39 | 6% | Other | 17 | 3% | Other | 25 | 4% | Other | 9 | 1% |
LS(DS=5) | F | % | LS(DS=6) | F | % | LS(DS=7) | F | % | LS(DS=8) | F | % |
7X1X3 | 213 | 33% | 6X1X1 | 205 | 32% | 6X2X6 | 203 | 30% | 2X5X1 | 278 | 44% |
6X5X1 | 153 | 24% | 6X4X1 | 154 | 24% | 6X4X6 | 156 | 23% | 1X5X3 | 156 | 25% |
1X1X6 | 78 | 12% | 1X2X6 | 73 | 11% | 1X3X14 | 148 | 22% | 2X4X1 | 71 | 11% |
1X1X3 | 68 | 11% | 6X5X1 | 69 | 11% | 6X2X3 | 138 | 21% | 2X2X6 | 59 | 9% |
7X2X3 | 55 | 9% | 6X2X1 | 60 | 9% | 7X5X14 | 12 | 2% | 2X1X1 | 56 | 9% |
1X1X4 | 37 | 6% | 6X4X3 | 58 | 9% | 6X3X3 | 4 | 1% | 2X3X1 | 16 | 3% |
Other | 32 | 5% | Other | 20 | 3% | Other | 8 | 1% | Other | 0 | 0% |