Parameter | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Run 6 |
---|---|---|---|---|---|---|
Cost function to optimize | CA | WCA | F1 | CA | WCA | F1 |
Number of epochs | 150 | 150 | 150 | 250 | 250 | 250 |
Number of prototypes | 1 | 1 | 1 | 5 | 5 | 5 |
Data point ratio per round | 0.75 | 0.75 | 0.75 | 0.75 | 0.75 | 0.75 |
Sigmoid sigma interval | [1.0,5.0] | [1.0,15.0] | [1.0,50.0] | [1.0,5.0] | [1.0,15.0] | [1.0,50.0] |
Prototype learning rate | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Matrix learning | True | True | True | True | True | True |
Omega learning rate | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Omega dimension | 27 | 27 | 27 | 27 | 27 | 27 |
Cost function beta | - | - | 1 | - | - | 1 |
Cost function weights | - | [0.75,0.25] | - | - | [0.75,0.25] | - |
Parallel execution | True | True | True | True | True | True |