Wrong estimator tags for LogisticRegression

Describe the bug

The estimator tags for sklearn.linear_model.LogisticRegression are wrong because the _get_tags method uses the following resolution order for this estimator:

from sklearn.linear_model import LogisticRegression
import inspect
list(reversed(inspect.getmro(LogisticRegression)))
[<class 'object'>, <class 'sklearn.linear_model._base.SparseCoefMixin'>, <class 'sklearn.base.ClassifierMixin'>, <class 'sklearn.linear_model._base.LinearClassifierMixin'>, <class 'sklearn.base.BaseEstimator'>, <class 'sklearn.linear_model._logistic.LogisticRegression'>]

Thus, sklearn.base.BaseEstimator is replacing the estimator tags defined in sklearn.base.ClassifierMixin (e.g., requires_y).

Steps/Code to Reproduce

from sklearn.linear_model import LogisticRegression
LogisticRegression()._get_tags()
{'requires_y': False, 'non_deterministic': False, 'requires_positive_X': False, 'requires_positive_y': False, 'X_types': ['2darray'], 'poor_score': False, 'no_validation': False, 'multioutput': False, 'allow_nan': False, 'stateless': False, 'multilabel': False, '_skip_test': False, '_xfail_checks': False, 'multioutput_only': False, 'binary_only': False, 'requires_fit': True}

Expected Results

{'requires_y': True, 'non_deterministic': False, 'requires_positive_X': False, 'requires_positive_y': False, 'X_types': ['2darray'], 'poor_score': False, 'no_validation': False, 'multioutput': False, 'allow_nan': False, 'stateless': False, 'multilabel': False, '_skip_test': False, '_xfail_checks': False, 'multioutput_only': False, 'binary_only': False, 'requires_fit': True}

Actual Results

{'requires_y': False, 'non_deterministic': False, 'requires_positive_X': False, 'requires_positive_y': False, 'X_types': ['2darray'], 'poor_score': False, 'no_validation': False, 'multioutput': False, 'allow_nan': False, 'stateless': False, 'multilabel': False, '_skip_test': False, '_xfail_checks': False, 'multioutput_only': False, 'binary_only': False, 'requires_fit': True}

Versions

import sklearn; sklearn.show_versions()

System:
    python: 3.6.10 (default, Jun  9 2020, 18:45:00)  [GCC 8.3.0]
executable: /usr/local/bin/python
   machine: Linux-4.19.76-linuxkit-x86_64-with-debian-10.4

Python dependencies:
          pip: 20.1.1
   setuptools: 47.1.1
      sklearn: 0.24.dev0
        numpy: 1.18.4
        scipy: 1.4.1
       Cython: 0.29.18
       pandas: 1.0.3
   matplotlib: 3.2.1
       joblib: 0.15.1
threadpoolctl: 2.0.0

Built with OpenMP: True

[rth]

better to do that in a separate PR.

@alfaro96 Including them in the PR that you just opened is also fine.

[alfaro96]

A few more located with:

$ grep -rnw "sklearn" -e ".*(BaseEstimator,.*"
sklearn/metrics/_plot/tests/test_plot_precision_recall.py:66:    class MyClassifier(BaseEstimator, ClassifierMixin):
sklearn/ensemble/tests/test_stacking.py:265:class NoWeightRegressor(BaseEstimator, RegressorMixin):
sklearn/ensemble/tests/test_stacking.py:274:class NoWeightClassifier(BaseEstimator, ClassifierMixin):
sklearn/ensemble/_hist_gradient_boosting/tests/test_gradient_boosting.py:395:    class MinMaxImputer(BaseEstimator, TransformerMixin):
sklearn/multioutput.py:63:class _MultiOutputEstimator(BaseEstimator, MetaEstimatorMixin,
sklearn/model_selection/tests/test_search.py:1824:    class TestEstimator(BaseEstimator, ClassifierMixin):

After removing the false positives (e.g., import) and the already found ones.