Following are the results of my implementation of RVErS algorithm on naive Bayes and C4.5 for sick-euthyroid and soybean datasets
| Data Set | Learning algorithm | Selection parameter | Iters | Subset Evals | Inputs | Time (sec) |
| sick-euthyroid | naive Bayes | rmax = 10 | 8 | 8 | 7 | 3.3 |
| rmax = 18 | 5 | 5 | 11 | 2.7 | ||
| rmax = 25 | 10 | 10 | 14 | 5.2 | ||
| sick-euthryoid | C4.5 | rmax = 10 | 21 | 21 | 21 | 31.7 |
| rmax = 18 | 18 | 18 | 21 | 27.9 | ||
| rmax = 25 | 6 | 6 | 16 | 23.9 | ||
| soybean | naive Bayes | rmax = 15 | NA | NA | NA | NA |
| rmax = 25 | 51 | 51 | 21 | 16.2 | ||
| rmax = 35 | 8 | 8 | 25 | 2.9 | ||
| soybean | C4.5 | rmax = 15 | 15 | 15 | 25 | 4.2 |
| rmax = 25 | 12 | 12 | 21 | 3.2 | ||
| rmax = 35 | 53 | 53 | 20 | 12.2 | ||
NA = not applicable because the experiment was terminated because of computational cost.