ENH NonBLASDotWarning -> EfficiencyWarning; Improve error message
DOC Add exceptions module to modules/classes.rst
MAINT Move ConvergenceWarning, UndefinedMetricWarning et al into exceptions
MAINT Remove ChangedBehaviorWarning from base
DOC/FIX Improve DataConversionWarning's docstring
Passing 1D arrays to check_array, without setting `ensure_2d` to false now
raises a deprecation warning before reshaping it. This will later throw an
error.
All Scaler classes also throw warnings when 1D arrays are passed.
All unit tests/doctests are modified to ensure that no 1D arrays are passed,
except in explicit 1D array tests where the warnings have been silenced.
Additional tests are also included which check for different 1D array cases.
2D array tests with one samples and one features are also added and where
they failed, `check_array` call has been modified to give a more useful error
message
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
I got this wrong all along: Cython functions that don't return Python
objects need an "except" clause to actually propagate exceptions (spotted
by @GaelVaroquaux, @arjoly).
Simplified memory management and unified error messages by safe_realloc.
The gini index and the mean square error (variance) might differ due
to numerical instability. Since those instabilities mainly occurs at
high tree depth, we restrict the maximal depth.
* avoid segfault (#2726) by setting base on numpy arrays
* A struct array for tree nodes and values array (size indeterminate at
compile time) are the only underlying structure, so each node is locally
grouped memory, and joblib dumps will save only two numpy files per
tree.
* predict() uses the value array's take method, reducing code repetition
seales