* Added override of fit_transform to LabelBinarizer
* Updated fit_transform to call base class method
* Changed fit_transform for code consistency
* Removed whitespace on blank lines
* Fixed line wrap issues for doc gen.
* Used line cont. for term defs
* Standardized bracket usage, fixed line cont. indent level
* BUG: MultiLabelBinarizer makes invalid CSR matrix
See https://github.com/scipy/scipy/issues/6719 for context.
The gist is that the `inverse` array may have a different dtype than `yt.indices`, which causes trouble down the line because, in those cases, `yt.indices` and `yt.indptr` have different dtypes.
Alternately, we could insert `yt.check_format(full_check=False)` after modifying the sparse matrix members.
* Fixing for old numpy
Older versions don't support kwargs for `astype`
* Adding tests
* line-wrapping
* adding comment to tests
[ci skip]
* added rationale comment
[ci skip]
* refer users to the other encoders to do one hot encoding for labels.
* added to the 'see more' for labelbinarizer, multilabelbinarizer, and labelencoder' as well as an example to multilabel binarizer
* added note about y labels to the OneHotEncoder docstring
* removed example from MultiLabelBinarizer
* documentation should specify LabelBinarizer, not MultiLabelBinarizer in OHE
MAINT Remove sequence of sequence support from datasets
MAINT Remove return_indicator param
MAINT Remove multilabel-seq test in OVR
MAINT Remove multilable-seq test in check_cv
MAINT Remove multilabel seq test in label_binarizer
TST type_of_target returns "unknown" for multilabel-sequence types
TST _check_targets should raise a ValueError
DOC show multilabel indicator as an example; remove return_indicator param
DOC use consistent lower case y for target
and fixes a few other doc problems while I was at it.
The main take-home message is to remember that you need a backslash when
your parameter type description exceeds one line.
fix dtype check, add test. unfriend all multi-output estimators on facebook.
try to fix what is happening to y (by doing nothing to y)
make test work...
Make everything accept object y or say "invalid label"
fix multioutput linear models
add test for sensible error message.
Roman Yurchak