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AttributeError: LogisticRegression `fit()` method broken with default solver( lbfgs ) for scikit-learn 0.23.2

See original GitHub issue

Describe the bug

In scikit-learn 0.23.2, LogisticRegression fit() method broken with default solver ( lbfgs )

Steps/Code to Reproduce

Log information :

Python 3.7.10 (default, Mar  1 2021, 12:53:44)
[GCC 7.5.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from sklearn.datasets import load_iris
>>> from sklearn.linear_model import LogisticRegression
>>>  X, y = load_iris(return_X_y=True)
>>> clf = LogisticRegression(random_state=0).fit(X, y)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/sklearn/linear_model/_logistic.py", line 1417, in fit
    for class_, warm_start_coef_ in zip(classes_, warm_start_coef))
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/joblib/parallel.py", line 1041, in __call__
    if self.dispatch_one_batch(iterator):
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/joblib/parallel.py", line 859, in dispatch_one_batch
    self._dispatch(tasks)
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/joblib/parallel.py", line 777, in _dispatch
    job = self._backend.apply_async(batch, callback=cb)
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/joblib/_parallel_backends.py", line 208, in apply_async
    result = ImmediateResult(func)
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/joblib/_parallel_backends.py", line 572, in __init__
    self.results = batch()
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/joblib/parallel.py", line 263, in __call__
    for func, args, kwargs in self.items]
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/joblib/parallel.py", line 263, in <listcomp>
    for func, args, kwargs in self.items]
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/sklearn/linear_model/_logistic.py", line 764, in _logistic_regression_path
    extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)
  File "/opt/miniconda3/envs/sklearn_test/lib/python3.7/site-packages/sklearn/utils/optimize.py", line 243, in _check_optimize_result
    ).format(solver, result.status, result.message.decode("latin1"))
AttributeError: 'str' object has no attribute 'decode'
>>>

Package versions:

python 3.7.10
scikit-learn 0.23.2

Issue Analytics

State:
Created 2 years ago
Comments:7 (5 by maintainers)

Top GitHub Comments

1reaction

NicolasHugcommented, Mar 31, 2021

Looks like the issue was introduced in scipy>=1.6.0, which was released after scikit-learn 0.23.2. Any chance you can downgrade scipy instead of upgrading scikit-learn?

0reactions

NicolasHugcommented, Apr 1, 2021

I was thinking the same, although it’s possible that

a) scipy broke backward compat but they issued a deprecation warning that we ignored b) we had been relying on a “private” thing (or something with no backward-compat guanrantee)

in which case an upper bound would not have helped (but IDK if any of these apply here).

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