def test_coef_table_multiple(self):
data = Table("zoo")
learn = LogisticRegressionLearner()
classifier = learn(data)
coef_table = create_coef_table(classifier)
self.assertEqual(1, len(stats(coef_table.metas, None)))
self.assertEqual(len(coef_table), len(classifier.domain.attributes) + 1)
self.assertEqual(len(coef_table[0]), len(classifier.domain.class_var.values))
def test_coef_table_single(self):
data = Table("titanic")
learn = LogisticRegressionLearner()
classifier = learn(data)
coef_table = create_coef_table(classifier)
self.assertEqual(1, len(stats(coef_table.metas, None)))
self.assertEqual(len(coef_table), len(classifier.domain.attributes) + 1)
self.assertEqual(len(coef_table[0]), 1)
def test_coef_table_single(self):
data = Table("titanic")
learn = LogisticRegressionLearner()
classifier = learn(data)
coef_table = create_coef_table(classifier)
self.assertEqual(1, len(stats(coef_table.metas, None)))
self.assertEqual(len(coef_table), len(classifier.domain.attributes) + 1)
self.assertEqual(len(coef_table[0]), 1)
def test_coef_table_multiple(self):
data = Table("zoo")
learn = LogisticRegressionLearner()
classifier = learn(data)
coef_table = create_coef_table(classifier)
self.assertEqual(1, len(stats(coef_table.metas, None)))
self.assertEqual(len(coef_table), len(classifier.domain.attributes) + 1)
self.assertEqual(len(coef_table[0]),
len(classifier.domain.class_var.values))
def update_model(self):
super().update_model()
coeffs = None
if self.model is not None:
if self.model.domain.class_var.is_discrete:
coeffs = create_coef_table(self.model)
else:
attrs = [ContinuousVariable("coef", number_of_decimals=7)]
domain = Domain(attrs, metas=[StringVariable("name")])
cfs = list(self.model.intercept) + list(self.model.coefficients)
names = ["intercept"] + \
[attr.name for attr in self.model.domain.attributes]
coeffs = Table(domain, list(zip(cfs, names)))
coeffs.name = "coefficients"
self.Outputs.coefficients.send(coeffs)
