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markotoplak  committed d1cc6a0

Added stubs of ICV and Stacking to the documentation

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  • Parent commits 5e0e4eb

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File docs/rst/Orange.evaluation.reliability.rst

 
 .. autoclass:: ParzenWindowDensityBased
 
+Internal cross validation (ICV)
+-------------------------------
+
+.. autoclass:: ICV
+
+
+Stacked generalization (Stacking)
+-------------------------------
+
+.. autoclass:: Stacking
+
 Reference Estimate for Classification (:math:`O_{ref}`)
 -------------------------------------------------------
 

File orangecontrib/reliability/__init__.py

 
         Name (string) of reliability estimation method used.
 
-    .. attribute:: icv_method
-
-        An integer ID of reliability estimation method that performed best,
-        as determined by ICV, and of which estimate is stored in the
-        :obj:`estimate` field. (:obj:`None` when ICV was not used.)
-
-    .. attribute:: icv_method_name
-
-        Name (string) of reliability estimation method that performed best,
-        as determined by ICV. (:obj:`None` when ICV was not used.)
-
     """
-    def __init__(self, estimate, signed_or_absolute, method, icv_method= -1):
+    def __init__(self, estimate, signed_or_absolute, method):
         self.estimate = estimate
         self.signed_or_absolute = signed_or_absolute
         self.method = method
         self.method_name = METHOD_NAME[method]
-        self.icv_method = icv_method
-        self.icv_method_name = METHOD_NAME[icv_method] if icv_method != -1 else ""
         self.text_description = None
 
 class DescriptiveAnalysis:
     use a lot of memory, as it build m of them, thereby using :math:`m` times memory
     for a single classifier. If instances for measuring predictions
     are given as a parameter, this class can only compute their reliability,
-    which allows less memory use. 
+    which saves memory. 
 
     """
     def __init__(self, m=50, name="bv", randseed=0, for_instances=None):