Hybridization of Machine Learning Models and Differential Evolution in Data Mining
Table 1: Comparison of the efficiency for approaches to identification based on the basis of GP algorithm
| Task number |
Basic approach |
Hybrid approach |
| 1 |
0.0013 |
0.0000 |
| 2 |
0.0072 |
0.0000 |
| 3 |
0.0037 |
0.0000 |
| 4 |
0.1047 |
0.0001 |
| 5 |
0.0077 |
0.0000 |
| 6 |
0.0983 |
0.0001 |
| 7 |
0.0065 |
0.0000 |
| 8 |
0.1200 |
0.0000 |
| 9 |
0.1742 |
0.0002 |
| 10 |
0.0084 |
0.0000 |
| 11 |
0.0035 |
0.0000 |
| 12 |
0.3202 |
0.0002 |
| 13 |
0.1462 |
0.0000 |
| 14 |
0.0893 |
0.0000 |
| 15 |
0.2540 |
0.0000 |
| 16 |
0.2985 |
0.0046 |
| 17 |
0.2562 |
0.0095 |
| 18 |
0.3724 |
0.0103 |
| 19 |
0.0566 |
0.0011 |
| 20 |
0.1499 |
0.0017 |
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