@@ -149,6 +149,12 @@ General Concepts
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introduces changes that are not backwards compatible, these are known
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as software regressions.
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+ callable
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+ A function, class or an object which implements the ``__call__ ``
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+ method; anything that returns True when the argument of
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+ `https://docs.python.org/3/library/functions.html#callable
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+ <callable()> `_.
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+
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categorical feature
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A categorical or nominal :term: `feature ` is one that has a
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finite set of discrete values across the population of data.
@@ -428,6 +434,10 @@ General Concepts
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hyper-parameter
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See :term: `parameter `.
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+ indexable
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+ An :term: `array-like `, :term: `sparse matrix `, pandas DataFrame or
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+ sequence (usually a list).
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+
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induction
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inductive
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Inductive (contrasted with :term: `transductive `) machine learning
@@ -441,6 +451,13 @@ General Concepts
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efficiently working with numpy arrays, such as through use of
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:term: `memory mapping `.
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+ label indicator matrix
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+ multilabel indicator matrix
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+ The format used to represent multilabel data, where each row of a 2d
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+ array or sparse matrix corresponds to a sample, each column
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+ corresponds to a class, and each element is 1 if the sample is labeled
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+ with the class and 0 if not.
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+
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leakage
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data leakage
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A problem in cross validation where generalization performance can be
@@ -520,6 +537,9 @@ General Concepts
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*tasks * or *targets *.
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See :term: `multiclass multioutput ` and :term: `continuous multioutput `.
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+ pair
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+ A tuple of length two.
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+
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parameter
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parameters
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param
@@ -667,7 +687,8 @@ General Concepts
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The sparse matrix is interpreted as an array with implicit and
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explicit zeros being interpreted as the number 0. This is the
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interpretation most often adopted, e.g. when sparse matrices
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- are used for feature matrices or multilabel indicator matrices.
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+ are used for feature matrices or :term: `multilabel indicator
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+ matrices `.
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graph semantics
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As with :mod: `scipy.sparse.csgraph `, explicit zeros are
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interpreted as the number 0, but implicit zeros indicate a masked
@@ -907,8 +928,9 @@ such as:
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.. glossary:
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- cross validation splitter
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+ cross- validation splitter
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CV splitter
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+ cross-validation generator
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A non-estimator family of classes used to split a dataset into a
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sequence of train and test portions (see :ref:`cross_validation`),
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by providing :term:`split` and :term:`get_n_splits` methods.
@@ -1361,7 +1383,7 @@ functions or non-estimator constructors.
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:term: `targets ` may represent a binary or multiclass (but not
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multioutput) classification problem (determined by
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:func: `utils.multiclass.type_of_target `).
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- - A :term: `cross validation splitter ` instance. Refer to the
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+ - A :term: `cross- validation splitter ` instance. Refer to the
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:ref: `User Guide <cross_validation >` for splitters available
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within Scikit-learn.
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- An iterable yielding train/test splits.
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