Hello! I used the sklearn genetic algorithm on random forest to find the best parameters:
genPar = {'num_estimators': Integer(100, 500), 'max_depth': Integer(8, 128),
'max_samples': Continuous(0.25, 0.9)}
It took about one day to complete and it was great; but when I apply it on Support Vector Machines it takes much more time:
genPar = {'kernel': Categorical(['linear', 'rbf']), 'C': Integer(1, 10),
'gamma': Integer(1, 10)}
Do you have any suggestion to speed-up the process?