Error with tuple hyperparameters

[psardin]

Hello @reiinakano

I have an issue with tuple hyperparameters. I think the bracket are ommited during the training

from gplearn.genetic import SymbolicRegressor base_learner = SymbolicRegressor(random_state=8,n_jobs=6)

params = {'function_set':('sqrt','add', 'sub', 'mul', 'div','max','min','log'), 'const_range':(-30, 280), 'init_depth':(6, 13) 'population_size': 150, 'generations': 600, 'stopping_criteria': 0.001, 'p_crossover': 0.45, 'p_subtree_mutation': 0.15, 'p_hoist_mutation': 0.15, 'p_point_mutation': 0.25, 'max_samples': 0.85, 'metric': 'rmse', 'parsimony_coefficient': 0.0002}

Traceback (most recent call last): File "/root/anaconda3/lib/python3.6/site-packages/xcessiv/rqtasks.py", line 135, in generate_meta_features est = est.fit(X_train, y_train) File "/root/anaconda3/lib/python3.6/site-packages/gplearn/genetic.py", line 366, in fit raise ValueError('const_range should be a tuple with length two.') ValueError: const_range should be a tuple with length two.

[reiinakano]

I have reproduced this error. Unfortunately, I currently do not have the time to look too deep into what is causing this. May I ask why you're trying to use xcessiv with gplearn? It seems like it would take up too much time as each gplearn estimator is doing its own optimization inside.

[psardin]

Im using gplearn as a base learner to add less correlated model to my ensemble (kaggle competition)