Research Article
A New Random Forest Algorithm Based on Learning Automata
Table 6
Friedman test statistical verification results for ranking the parameters of reward and penalty and comparing the proposed method with the literature.
| Method | Tuning | Mean rank | Final rank |
| LRP | a = 0.5, b = 0.5 | 19.17 | 1 | LRP | a = 0.3, b = 0.3 | 16.83 | 2 | LRP | a = 0.7, b = 0.7 | 15.58 | 3 | MV | Majority voting | 14.67 | 4 | LRP | a = 0.1, b = 0.1 | 13.92 | 5 | LReP | a = 0.05, b = 0.01 | 12.17 | 6 | LReP | a = 0.1, b = 0.01 | 11.83 | 7 | LReP | a = 0.5, b = 0.01 | 10.08 | 8 | LRP | a = 0.05, b = 0.05 | 9.58 | 9 | RF | Random forest | 9.17 | 10 | LRP | a = 0.01, b = 0.01 | 8.75 | 11 | LIR | a = 0.01, b = 0 | 8.42 | 12 | LIR | a = 0.05, b = 0 | 7.67 | 13 | LIR | a = 0.1, b = 0 | 7.67 | 13 | LIR | a = 0.3, b = 0 | 7.67 | 13 | LIR | a = 0.5, b = 0 | 7.67 | 13 | LIR | a = 0.7, b = 0 | 7.67 | 13 | AV | Averaging | 7.58 | 14 | LReP | a = 0.3, b = 0.01 | 7.17 | 15 | LReP | a = 0.7, b = 0.01 | 6.75 | 16 |
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