Closed
Description
Description
TypeError: Singleton array array(True) cannot be considered a valid collection.
Steps/Code to Reproduce
Found when running RandomizedSearchCV with LightGBM. Previously worked fine. Latest update requires that all the **fit_params be checked for 'slicability'. Difficult when some fit params are things like early_stopping_rounds = 5.
#Import the modules
import lightgbm as lgb
from sklearn.model_selection import RandomizedSearchCV
from sklearn.model_selection import GridSearchCV
#Create parameters grid
#Create fixed parameters
mod_fixed_params = {
'boosting_type':'gbdt'
,'random_state':0
,'silent':False
,'objective':'multiclass'
,'num_class':np.unique(y_train)
,'min_samples_split':200 #Should be between 0.5-1% of samples
,'min_samples_leaf':50
,'subsample':0.8
}
search_params = {
'fixed':{
'cv':3
,'n_iter':80
,'verbose':True
,'random_state':0
}
,'variable':{
'learning_rate':[0.1,0.01,0.005]
,'num_leaves':np.linspace(10,1010,100,dtype=int)
,'max_depth':np.linspace(2,22,10,dtype=int)
}
}
fit_params = {
'verbose':True
,'eval_set':[(X_valid,y_valid)]
,'eval_metric':lgbm_custom_loss
,'early_stopping_rounds':5
}
#Setup the model
lgb_mod = lgb.LGBMClassifier(**mod_fixed_params)
#Add the search grid
seed = np.random.seed(0)
gbm = RandomizedSearchCV(lgb_mod,search_params['variable'],**search_params['fixed'])
#Fit the model
gbm.fit(X_train,y_train,**fit_params)
print('Best parameters found by grid search are: {}'.format(gbm.best_params_))I've traced the error through and it starts in model_selection/_search.py ln652
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Expected Results
Expected to run the LightGBM wthrough RandomSearchGrid
Actual Results
TypeError: Singleton array array(True) cannot be considered a valid collection.