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fixed bug at ClimbsRocks#417
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mohataher authored and mohataher committed Nov 1, 2018
1 parent 4b7e0e7 commit d75e0c2
Showing 1 changed file with 6 additions and 1 deletion.
7 changes: 6 additions & 1 deletion auto_ml/predictor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,6 +59,11 @@ def _pickle_method(m):
copyreg.pickle(types.MethodType, _pickle_method)


class ExtendedEvolutionaryAlgorithmSearchCV(EvolutionaryAlgorithmSearchCV):
def _run_search(cls):
"""required method on base class but not implemented; it causes a TypeError"""
pass

class Predictor(object):


Expand Down Expand Up @@ -1131,7 +1136,7 @@ def fit_grid_search(self, X_df, y, gs_params, feature_learning=False, refit=Fals
fit_evolutionary_search = True
# For some reason, EASCV doesn't play nicely with CatBoost. It blows up the memory hugely, and takes forever to train
if fit_evolutionary_search == True:
gs = EvolutionaryAlgorithmSearchCV(
gs = ExtendedEvolutionaryAlgorithmSearchCV(
# Fit on the pipeline.
ppl,
# Two splits of cross-validation, by default
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1 comment on commit d75e0c2

@chjq201410695
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thanks for fixing the bug. But it does not work on my machine yet. the error as below:

TypeError Traceback (most recent call last)
in ()
11 'SGDClassifier'],
12 cv=4, feature_learning=False,fl_data = train_fl,
---> 13 prediction_intervals=True,compare_all_models=True)
14
15 ml_predictor.score(test, test.book)

~/.conda/envs/ML_DNN/lib/python3.6/site-packages/auto_ml/predictor.py in train(failed resolving arguments)
668
669 self.set_scoring(y)
--> 670
671 if self.X_test is not None and self.X_test_already_transformed == False:
672 self.X_test = self.transformation_pipeline.transform(self.X_test)

~/.conda/envs/ML_DNN/lib/python3.6/site-packages/auto_ml/predictor.py in train_ml_estimator(self, estimator_names, scoring, X_df, y, feature_learning, prediction_interval)
1267
1268 grid_search_params = self.create_gs_params(model_name)
-> 1269 # Adding model name to gs params just to help with logging
1270 grid_search_params['model'] = [utils_models.get_model_from_name(model_name)]
1271 # grid_search_params['model_name'] = model_name

~/.conda/envs/ML_DNN/lib/python3.6/site-packages/auto_ml/predictor.py in fit_grid_search(self, X_df, y, gs_params, feature_learning, refit)
1154 pre_dispatch='1.5*n_jobs',
1155 # The number of
-> 1156 population_size=population_size,
1157 gene_mutation_prob=gene_mutation_prob,
1158 tournament_size=tournament_size,

TypeError: Can't instantiate abstract class EvolutionaryAlgorithmSearchCV with abstract methods _run_search

Is there any other advise? Thanks again.

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