def test_perceptron():
iris = DataSet(name="iris")
iris.classes_to_numbers()
classes_number = len(iris.values[iris.target])
perceptron = PerceptronLearner(iris)
tests = [([5, 3, 1, 0.1], 0), ([6, 3, 4, 1.1], 1), ([7.5, 4, 6, 2], 2)]
assert grade_learner(perceptron, tests) >= 2
def test_neural_network_learner():
iris = DataSet(name="iris")
classes = ["setosa", "versicolor", "virginica"]
iris.classes_to_numbers(classes)
nNL = NeuralNetLearner(iris, [5], 0.15, 75)
tests = [([5, 3, 1, 0.1], 0), ([6, 3, 3, 1.5], 1), ([7.5, 4, 6, 2], 2)]
assert grade_learner(nNL, tests) >= 2
def test_neural_network_learner():
iris = DataSet(name="iris")
classes = ["setosa","versicolor","virginica"]
iris.classes_to_numbers(classes)
nNL = NeuralNetLearner(iris, [5], 0.15, 75)
tests = [([5, 3, 1, 0.1], 0),
([5, 3.5, 1, 0], 0),
([6, 3, 4, 1.1], 1),
([6, 2, 3.5, 1], 1),
([7.5, 4, 6, 2], 2),
([7, 3, 6, 2.5], 2)]
assert grade_learner(nNL, tests) >= 2/3
assert err_ratio(nNL, iris) < 0.25
def test_perceptron():
iris = DataSet(name="iris")
iris.classes_to_numbers()
classes_number = len(iris.values[iris.target])
perceptron = PerceptronLearner(iris)
tests = [([5, 3, 1, 0.1], 0),
([5, 3.5, 1, 0], 0),
([6, 3, 4, 1.1], 1),
([6, 2, 3.5, 1], 1),
([7.5, 4, 6, 2], 2),
([7, 3, 6, 2.5], 2)]
assert grade_learner(perceptron, tests) > 1/2
assert err_ratio(perceptron, iris) < 0.4