Hybrid Gradient Descent Grey Wolf Optimizer for Optimal Feature Selection

Pseudocode 5

Implementation 2.

1. Function mutation with partial derivative

2. Pass in: wolf_pos, derivatives, probability threshold, a

3. Set weight as 0.4a + 0.1

4. Normalize the partial derivative

5. Calculate the sigmoid of the normalized partial derivative and set to variable sig

6. Use probability threshold and weight to choose the feature indices to change

7. Calculate the new wolf position and pass back