Ignore:
Location:
Orange
Files:
4 edited

Legend:

Unmodified
Added
Removed
  • Orange/clustering/kmeans.py

    r9725 r9977  
    176176score_distance_to_centroids.minimize = True 
    177177 
    178 def score_conditionalEntropy(km): 
     178def score_conditional_entropy(km): 
    179179    """UNIMPLEMENTED cluster quality measured by conditional entropy""" 
    180     pass 
    181  
    182 def score_withinClusterDistance(km): 
     180    raise NotImplemented 
     181 
     182def score_within_cluster_distance(km): 
    183183    """UNIMPLEMENTED weighted average within-cluster pairwise distance""" 
    184     pass 
    185  
    186 score_withinClusterDistance.minimize = True 
    187  
    188 def score_betweenClusterDistance(km): 
     184    raise NotImplemented 
     185 
     186score_within_cluster_distance.minimize = True 
     187 
     188def score_between_cluster_distance(km): 
    189189    """Sum of distances from elements to 'nearest miss' centroids""" 
    190190    return sum(min(km.distance(c, d) for j,c in enumerate(km.centroids) if j!=km.clusters[i]) for i,d in enumerate(km.data)) 
     191 
     192from Orange.misc import deprecated_function_name 
     193score_betweenClusterDistance = deprecated_function_name(score_between_cluster_distance) 
    191194 
    192195def score_silhouette(km, index=None): 
  • Orange/clustering/mixture.py

    r9919 r9976  
    277277    """ Computes the gaussian mixture model from an Orange data-set. 
    278278    """ 
    279     def __new__(cls, data=None, weightId=None, **kwargs): 
     279    def __new__(cls, data=None, weight_id=None, **kwargs): 
    280280        self = object.__new__(cls) 
    281281        if data is not None: 
    282282            self.__init__(**kwargs) 
    283             return self.__call__(data, weightId) 
     283            return self.__call__(data, weight_id) 
    284284        else: 
    285285            return self 
     
    289289        self.init_function = init_function 
    290290         
    291     def __call__(self, data, weightId=None): 
     291    def __call__(self, data, weight_id=None): 
    292292        from Orange.preprocess import Preprocessor_impute, DomainContinuizer 
    293293#        data = Preprocessor_impute(data) 
  • Orange/testing/unit/tests/test_association.py

    r9679 r9979  
    1414         
    1515    self.assertLessEqual(len(rules), self.inducer.max_item_sets) 
    16     print "\n%5s   %5s" % ("supp", "conf") 
    1716    for r in rules: 
    18         print "%5.3f   %5.3f   %s" % (r.support, r.confidence, r) 
    1917        self.assertGreaterEqual(r.support, self.inducer.support) 
    2018        self.assertIsNotNone(r.left) 
  • Orange/testing/unit/tests/test_ensemble.py

    r9679 r9978  
    2323        testing.LearnerTestCase.test_pickling_on(self, dataset) 
    2424 
     25 
    2526@datasets_driven(datasets=testing.CLASSIFICATION_DATASETS) 
    2627class TestRandomForest(testing.LearnerTestCase): 
     
    3132    @test_on_datasets(datasets=["iris"]) 
    3233    def test_pickling_on(self, dataset): 
    33         testing.LearnerTestCase.test_pickling_on(self, dataset) 
     34        raise NotImplemented("SmallTreeLearner pickling is not implemented") 
     35#        testing.LearnerTestCase.test_pickling_on(self, dataset) 
     36         
    3437         
    3538         
Note: See TracChangeset for help on using the changeset viewer.