def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.same_input_output_domain = False cls.signal_name = "Data" cls.signal_data = cls.data
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.signal_name = "Distances" cls.signal_data = Euclidean(cls.data) cls.same_input_output_domain = False
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.signal_name = "Data" cls.signal_data = cls.data cls.scorename = "Silhouette ({})".format(cls.data.domain.class_var.name)
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.signal_name = "Data" cls.signal_data = cls.data cls.titanic = Table("titanic") cls.iris = Table("iris")
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) tree = TreeLearner() cls.model = tree(cls.data) cls.model.instances = cls.data cls.signal_name = "Tree" cls.signal_data = cls.model
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.signal_name = "Distances" cls.signal_data = Euclidean(cls.data) cls.same_input_output_domain = False my_dir = os.path.dirname(__file__) datasets_dir = os.path.join(my_dir, '..', '..', '..', 'datasets') cls.datasets_dir = os.path.realpath(datasets_dir)
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.iris = Table("iris") cls.zoo = Table("zoo") cls.housing = Table("housing") cls.titanic = Table("titanic") cls.heart = Table("heart_disease") cls.data = cls.iris cls.signal_name = "Data" cls.signal_data = cls.data
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.titanic = Table('titanic') cls.learner = CN2Learner() cls.classifier = cls.learner(cls.titanic) # CN2Learner does not add `instances` attribute to the model, but # the Rules widget does. We simulate the model we get from the widget. cls.classifier.instances = cls.titanic cls.signal_name = "Classifier" cls.signal_data = cls.classifier cls.data = cls.titanic
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) bayes = NaiveBayesLearner() tree = TreeLearner() iris = cls.data titanic = Table("titanic") common = dict(k=3, store_data=True) cls.results_1_iris = CrossValidation(iris, [bayes], **common) cls.results_2_iris = CrossValidation(iris, [bayes, tree], **common) cls.results_2_titanic = CrossValidation(titanic, [bayes, tree], **common) cls.signal_name = "Evaluation Results" cls.signal_data = cls.results_1_iris cls.same_input_output_domain = False
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) tree = TreeLearner() cls.model = tree(cls.data) cls.model.instances = cls.data cls.signal_name = "Tree" cls.signal_data = cls.model # Load a dataset that contains two variables with the same entropy data_same_entropy = Table(path.join( path.dirname(path.dirname(path.dirname(__file__))), "tests", "datasets", "same_entropy.tab")) cls.data_same_entropy = tree(data_same_entropy) cls.data_same_entropy.instances = data_same_entropy
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) # Set up for output tests tree = TreeLearner() cls.model = tree(cls.data) cls.model.instances = cls.data cls.signal_name = "Tree" cls.signal_data = cls.model # Set up for widget tests titanic_data = Table('titanic')[::50] cls.titanic = TreeLearner(max_depth=1)(titanic_data) cls.titanic.instances = titanic_data housing_data = Table('housing')[:10] cls.housing = TreeLearner(max_depth=1)(housing_data) cls.housing.instances = housing_data
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.signal_name = "Data" cls.signal_data = cls.data
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.signal_name = "Distances" cls.signal_data = Euclidean(cls.data)
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls, output_all_on_no_selection=True) cls.signal_name = "Data" cls.signal_data = cls.data # pylint: disable=no-member
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.same_input_output_domain = False cls.signal_name = "Data"
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls) cls.signal_name = "Data" cls.signal_data = cls.data # pylint: disable=no-member
def setUpClass(cls): super().setUpClass() WidgetOutputsTestMixin.init(cls, False) cls.signal_data = cls.data[:25]