ImportError: cannot import name 'parallel_helper'
ImportError: cannot import name 'parallel_helper'
每当我 运行 - from sklearn.ensemble import RandomForestClassifier
我遇到错误 - ImportError: cannot import name 'parallel_helper'
堆栈跟踪是 -
--------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-135-d80da5c856d8> in <module>()
1 # feature removal using ROC-AUC score
----> 2 from sklearn.ensemble import RandomForestClassifier
3 roc_values = []
4 for feature in diabetes_MICE_X.columns:
5 clf = RandomForestClassifier()
~/anaconda3/envs/python3/lib/python3.6/site-packages/sklearn/ensemble/__init__.py in <module>()
5
6 from .base import BaseEnsemble
----> 7 from .forest import RandomForestClassifier
8 from .forest import RandomForestRegressor
9 from .forest import RandomTreesEmbedding
~/anaconda3/envs/python3/lib/python3.6/site-packages/sklearn/ensemble/forest.py in <module>()
59 from ..exceptions import DataConversionWarning, NotFittedError
60 from .base import BaseEnsemble, _partition_estimators
---> 61 from ..utils.fixes import parallel_helper, _joblib_parallel_args
62 from ..utils.multiclass import check_classification_targets
63 from ..utils.validation import check_is_fitted
ImportError: cannot import name 'parallel_helper'
Note - I'm using jupyter notebook (conda_python3) in sagemaker.
scipy version = 1.3.1
numpy version = 1.17.2
scikit version = 0.21.3
one strange thing that i'm unable to figure out is - whenever i do
import sklearn
sklearn.__version__
它给我的输出是 0.22
有人可以帮我解决这个问题吗?
最好的办法是重新启动内核。我在 google colab 上有过类似的经历,重启运行时解决了问题。
在 sagemaker 中克服这个问题的最好方法是使用生命周期配置。
不要在 notebook 中执行 pip install,而是将所有 requirements.txt 安装写在生命周期配置中。笔记本将花费更多时间生成,但代码和库将是 pre-installed.
每当我 运行 - from sklearn.ensemble import RandomForestClassifier
我遇到错误 - ImportError: cannot import name 'parallel_helper'
堆栈跟踪是 -
--------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-135-d80da5c856d8> in <module>()
1 # feature removal using ROC-AUC score
----> 2 from sklearn.ensemble import RandomForestClassifier
3 roc_values = []
4 for feature in diabetes_MICE_X.columns:
5 clf = RandomForestClassifier()
~/anaconda3/envs/python3/lib/python3.6/site-packages/sklearn/ensemble/__init__.py in <module>()
5
6 from .base import BaseEnsemble
----> 7 from .forest import RandomForestClassifier
8 from .forest import RandomForestRegressor
9 from .forest import RandomTreesEmbedding
~/anaconda3/envs/python3/lib/python3.6/site-packages/sklearn/ensemble/forest.py in <module>()
59 from ..exceptions import DataConversionWarning, NotFittedError
60 from .base import BaseEnsemble, _partition_estimators
---> 61 from ..utils.fixes import parallel_helper, _joblib_parallel_args
62 from ..utils.multiclass import check_classification_targets
63 from ..utils.validation import check_is_fitted
ImportError: cannot import name 'parallel_helper'
Note - I'm using jupyter notebook (conda_python3) in sagemaker.
scipy version = 1.3.1
numpy version = 1.17.2
scikit version = 0.21.3
one strange thing that i'm unable to figure out is - whenever i do
import sklearn
sklearn.__version__
它给我的输出是 0.22
有人可以帮我解决这个问题吗?
最好的办法是重新启动内核。我在 google colab 上有过类似的经历,重启运行时解决了问题。
在 sagemaker 中克服这个问题的最好方法是使用生命周期配置。 不要在 notebook 中执行 pip install,而是将所有 requirements.txt 安装写在生命周期配置中。笔记本将花费更多时间生成,但代码和库将是 pre-installed.