def testLearnClassify(self): docs = getDocs() l = Learner() class_values = [1, 1, 1, -1, -1] model = l.learn(docs, class_values) judgments = [model.classify(d) for d in docs] for i in range(len(class_values)): binary = 1 if judgments[i] > 0 else -1 self.assertEqual(class_values[i], binary)
def testLearn(self): docs = getDocs() l = Learner() model = l.learn(docs, [1, 1, 1, -1, -1]) print model, model.bias self.assertEqual(5, model.num_docs) self.assertEqual(10, len(model.plane)) self.assertNotEqual(model.bias, 0) print model.plane
def testLearnUnbiased(self): docs = getDocs() l = Learner() l.biased_hyperplane = False model = l.learn(docs, [1, 1, 1, -1, -1]) print model, model.bias self.assertEqual(5, model.num_docs) self.assertEqual(10, len(model.plane)) self.assertEqual(model.bias, 0) print model.plane
def testSetBiasedHyperplane(self): l = Learner() l.biased_hyperplane = False self.assertEqual(str(l), "Learner(biased_hyperplane=False)")
def testConstruction(self): self.assertEqual(str(Learner()), "Learner(biased_hyperplane=True)")
def test_set_biased_hyperplane(self): l = Learner() l.biased_hyperplane = False self.assertEqual(str(l), 'Learner(biased_hyperplane=False)')