* some bug fixes.
* minor fixes to whatsnew
* typo in whatsnew
* add test for n_components = 1 transform in dict learning
* feature extraction doc fix
* fix broken test
* revert aggressive input validation changes
* in SelectFromModel, don't store threshold_ in transform. If we called "fit", use estimates from last "fit".
* move score from EllipticEnvelope to OutlierDetectionMixin
* revert changes to Tfidf documentation
* remove dummy input validation from whatsnew
* fix text feature tests
* rewrite from_model threshold again...
* remove stray condition
* fix self.estimator -> estimator, slightly more interesting test
* typo in comment
* Fix issues in SparseEncoder, add tests.
more explicit explanation of SparseEncoder change, add issue numbers to whatsnew
* minor fixes in whats_new.rst
* slightly more consistency with tuples for shapes
* not longer typo
* Documentation: Add xcessiv to related projects
For your consideration, this adds Xcessiv to the list of related projects under experimentation frameworks. Xcessiv lets you fully define your data, cross-validation technique, estimators, and metrics and is based heavily on the scikit-learn API.
* Modify second sentence
* #8477
check length of feature_names in export_graphviz
- raise ValueError if len(feature_names) > tree.n_features
- add unit test for len(feature_names) > tree.n_features
- change the comment of existing unit test for len(feature_names) <
tree.n_features
* fix error and warning
- include length of feature_names and number of features in tree in the
error and warning message.
- raise error for too few feature_names
- for too much feature_names, will use the first n_features. raise an
warning for users
- use assert_raise_message and assert_warns_message in test to check
message.
* move the error and warning from node_to_str to export_graphviz so it will fail early for wrong length of feature_names
* raise error if length of feature_names does not match number of features in the decision tree
* fix pep8
* remove unused assert_warns_message import in test_export.py
* add bug fix in doc/whats_new.rst
* fix the english in doc/whats_new.rst
* fix the format and english in sklearn/tree/export.py
* fix contributor format in doc/whats_new.rst
* fix english, use bracket and avoid \ in error message
* fix pep8
* fix pep8
* PR to 7288
Use _BaseComposition as base
* Fix flakes problem
* Change ``pipeline``, add more tests and other changes
1. Use ``_BaseComposition`` in class ``Pipeline`` and ``FeatureUnion``
2. Add tests of soft voting ``transform`` when one estimator is set to None
3. Add estimator name validation in ``_BaseComposition`` and tests
4. Other requested changes.
* Remove the unused import warn
* Add more test and documentation
* resolve conflict with master
* Add testing cases and modify documentation
* Add to whats_new.rst
* Fix too many blank lines
* Added predict method to class OneClassSVM
- This method overrides the default behaviour to only return integer class values.
* Test for the change in OneClassSVM predict method
- small addition to test that the predicted result is integer
* Changed test to check for intp datatype
* Updated whats new
* Change named_steps to Bunch object
* Update named_steps attribute documentation
* Add test for named steps bunch object
* Delete whitespace in test_pipeline
* Update test_pipeline.py
* Add comment for named_steps usage
* Move dataset/Bunch to utils
* Fix to PEP8 format
* Add __getattribute method to Bunch class, Fix pep8 bug
* Remove __getattribute__, update test_pipeline
* Update test with conflict and non-conflict named_steps
* Add reference to class Pipeline
Remi Rampin
Hanmin Qin