I am using automatminer from the debug preset.
I often see the following results:
ValueError: Found array with 0 feature(s) (shape=(508, 0)) while a minimum of 1 is required.
I see it with the express preset as well.
Full stack trace:
Traceback (most recent call last):
File “test_636.py”, line 15, in
predicted_folds = pipe.benchmark(df, “exfoliation_en”, kf)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/automatminer/utils/pkg.py”, line 104, in wrapper
result = func(*args, **kwargs)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/automatminer/pipeline.py”, line 336, in benchmark
self.fit(train, target)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/automatminer/utils/pkg.py”, line 104, in wrapper
result = func(*args, **kwargs)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/automatminer/pipeline.py”, line 184, in fit
self.learner.fit(df, target)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/automatminer/utils/log.py”, line 96, in wrapper
result = meth(*args, **kwargs)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/automatminer/utils/pkg.py”, line 104, in wrapper
result = func(*args, **kwargs)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/automatminer/automl/adaptors.py”, line 137, in fit
self._backend = self._backend.fit(X, y, **fit_kwargs)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/tpot/base.py”, line 746, in fit
raise e
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/tpot/base.py”, line 738, in fit
self._summary_of_best_pipeline(features, target)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/tpot/base.py”, line 862, in summary_of_best_pipeline
self.pareto_front_fitted_pipelines[str(pipeline)].fit(features, target)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/sklearn/pipeline.py”, line 350, in fit
Xt, fit_params = self._fit(X, y, **fit_params)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/sklearn/pipeline.py”, line 315, in _fit
**fit_params_steps[name])
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/joblib/memory.py”, line 591, in call
return self._cached_call(args, kwargs)[0]
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/joblib/memory.py”, line 534, in _cached_call
out, metadata = self.call(*args, **kwargs)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/joblib/memory.py”, line 761, in call
output = self.func(*args, **kwargs)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/sklearn/pipeline.py”, line 728, in _fit_transform_one
res = transformer.fit_transform(X, y, **fit_params)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/sklearn/base.py”, line 574, in fit_transform
return self.fit(X, y, **fit_params).transform(X)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/sklearn/kernel_approximation.py”, line 545, in fit
X = check_array(X, accept_sparse=‘csr’)
File “/root/anaconda3/envs/automatminer/lib/python3.6/site-packages/sklearn/utils/validation.py”, line 594, in check_array
context))