@@ -35,20 +35,6 @@ def test_weighted_replicate():
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assert weighted_replicate ('ABC' , [1 , 2 , 1 ], 4 ) == ['A' , 'B' , 'B' , 'C' ]
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- def test_means_and_deviation ():
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- iris = DataSet (name = "iris" )
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-
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- means , deviations = iris .find_means_and_deviations ()
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-
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- assert means ["setosa" ] == [5.006 , 3.418 , 1.464 , 0.244 ]
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- assert means ["versicolor" ] == [5.936 , 2.77 , 4.26 , 1.326 ]
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- assert means ["virginica" ] == [6.588 , 2.974 , 5.552 , 2.026 ]
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-
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- assert round (deviations ["setosa" ][0 ],3 ) == 0.352
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- assert round (deviations ["versicolor" ][0 ],3 ) == 0.516
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- assert round (deviations ["virginica" ][0 ],3 ) == 0.636
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-
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-
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def test_plurality_learner ():
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zoo = DataSet (name = "zoo" )
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@@ -63,11 +49,6 @@ def test_naive_bayes():
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nBD = NaiveBayesLearner (iris )
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assert nBD ([5 ,3 ,1 ,0.1 ]) == "setosa"
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- # Continuous
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- nBC = NaiveBayesLearner (iris , continuous = True )
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- assert nBC ([5 ,3 ,1 ,0.1 ]) == "setosa"
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- assert nBC ([7 ,3 ,6.5 ,2 ]) == "virginica"
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-
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def test_k_nearest_neighbors ():
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iris = DataSet (name = "iris" )
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