:obj:`~Orange.classification.ClassifierFromVar` and :obj:`~Orange.classification.ClassifierFromVarFD` are helper classifiers used to compute variable's values from another variables. They are used, for instance, in discretization of continuous variables.
:obj:`~Orange.classification.ClassifierFromVarFD` retrieves the feature value based on its position in the domain and :obj:`~Orange.classification.ClassifierFromVar` retrieves the feature with the given descriptor.
Both classifiers can be given a function to transform the value. In discretization, for instance, the transformer computes the corresponding discrete interval for a continuous value of the original variable.
Return the value of variable :obj:`~ClassifierFromVar.which_var`; transform it by the :obj:`~ClassifierFromVar.transformer`, if it is given.
.. attribute:: which_var
The descriptor of the feature whose value is returned.
.. attribute:: transformer
The transformer for the value. It should be a class derived
from :obj:`~Orange.data.utils.TransformValue` or a function
written in Python.
.. attribute:: transform_unknowns
Defines the treatment of missing values.
.. attribute:: distribution_for_unknown
The distribution that is returned when the
:obj:`~ClassifierFromVar.which_var`'s value is undefined and
:obj:`~ClassifierFromVar.transform_unknowns` is ``False``.
.. method:: __call__(inst[, result_type])
Return ``transformer(instance[which_var])``. The value of
:obj:`~ClassifierFromVar.which_var` can be either an ordinary
variable, a meta variable or a variable which is not defined
for the instance but its descriptor has a
:obj:`~Orange.feature.Descriptor.get_value_from` that can be
used to compute the value.
If the feature is not found or its value is missing, the
missing value is passed to the transformer if
:obj:`~ClassifierFromVar.transform_unknowns` is
``True``. Otherwise,
:obj:`~ClassifierFromVar.distribution_for_unknown` is
returned.
The following example demonstrates the use of the class on the Monk 1 dataset. It construct a new variable e1 that has a value of 1, when e is 1, and not 1 otherwise.
.. literalinclude:: code/classifier-from-var-example.py
:lines: 1-19
A class similar to :obj:`~Orange.classification.ClassifierFromVar` except that the variable is given by its index in the domain. The index can also be negative to denote a meta attribute.
The only practical difference between the two classes is that this does not compute the value of the variable from other variables through the descriptor's :obj:`Orange.feature.Descriptor.get_value_from`.
.. attribute:: domain (inherited from :obj:`ClassifierFromVarFD`)
The domain to which the :obj:`position` applies.
.. attribute:: position
The position of the attribute in the domain or its meta-id.
.. attribute:: transformer
The transformer for the value. It should be a class derived
from :obj:`Orange.data.utils.TransformValue` or a function
written in Python.
.. attribute:: transform_unknowns
Defines the treatment of missing values.
.. attribute:: distribution_for_unknown
The distribution that is returned when the `which_var`'s value
is undefined and :obj:`transform_unknowns` is ``False``.
The use of this class is similar to that of :obj:`~Orange.classification.ClassifierFromVar`.
.. literalinclude:: code/classifier-from-var-example.py
:lines: 21-25