[MRG] DOC add entries missing from glossary
With thanks to the demo of
@@ -149,6 +149,11 @@ General Concepts
introduces changes that are not backwards compatible, these are known
as software regressions.
+ callable
+ A function, class or an object which implements the ``__call__``
+ method; anything that returns True when the argument of `callable()
+ <https://docs.python.org/3/library/functions.html#callable>`_.
+
categorical feature
A categorical or nominal :term:`feature` is one that has a
finite set of discrete values across the population of data.
@@ -428,6 +433,10 @@ General Concepts
hyper-parameter
See :term:`parameter`.
+ indexable
+ An :term:`array-like`, :term:`sparse matrix`, pandas DataFrame or
+ sequence (usually a list).
+
induction
inductive
Inductive (contrasted with :term:`transductive`) machine learning
@@ -441,6 +450,13 @@ General Concepts
efficiently working with numpy arrays, such as through use of
:term:`memory mapping`.
+ label indicator matrix
+ multilabel indicator matrix
+ The format used to represent multilabel data, where each row of a 2d
+ array or sparse matrix corresponds to a sample, each column
+ corresponds to a class, and each element is 1 if the sample is labeled
+ with the class and 0 if not.
+
leakage
data leakage
A problem in cross validation where generalization performance can be
@@ -520,6 +536,9 @@ General Concepts
*tasks* or *targets*.
See :term:`multiclass multioutput` and :term:`continuous multioutput`.
+ pair
+ A tuple of length two.
+
parameter
parameters
param
@@ -667,7 +686,8 @@ General Concepts
The sparse matrix is interpreted as an array with implicit and
explicit zeros being interpreted as the number 0. This is the
interpretation most often adopted, e.g. when sparse matrices
- are used for feature matrices or multilabel indicator matrices.
+ are used for feature matrices or :term:`multilabel indicator
+ matrices`.
graph semantics
As with :mod:`scipy.sparse.csgraph`, explicit zeros are
interpreted as the number 0, but implicit zeros indicate a masked
@@ -907,8 +927,9 @@ such as:
.. glossary:
- cross validation splitter
+ cross-validation splitter
CV splitter
+ cross-validation generator
A non-estimator family of classes used to split a dataset into a
sequence of train and test portions (see :ref:`cross_validation`),
by providing :term:`split` and :term:`get_n_splits` methods.
@@ -1361,7 +1382,7 @@ functions or non-estimator constructors.
:term:`targets` may represent a binary or multiclass (but not
multioutput) classification problem (determined by
:func:`utils.multiclass.type_of_target`).
- - A :term:`cross validation splitter` instance. Refer to the
+ - A :term:`cross-validation splitter` instance. Refer to the
:ref:`User Guide <cross_validation>` for splitters available
within Scikit-learn.
- An iterable yielding train/test splits.
