def test_iterate_gradient(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
capturedOutput = io.StringIO()
sys.stdout = capturedOutput
regression.iterate_gradient(dataset,
cols=[1, 8],
betas=[400, -400, 300],
T=10,
eta=1e-4)
output = capturedOutput.getvalue()
output_lines = output.split('\n')
sys.stdout = sys.__stdout__
expected_lines = [
"1 423085332.40 394.45 -405.84 -220.18",
"2 229744495.73 398.54 -401.54 163.14",
"3 124756241.68 395.53 -404.71 -119.33",
"4 67745350.04 397.75 -402.37 88.82",
"5 36787203.39 396.11 -404.09 -64.57",
"6 19976260.50 397.32 -402.82 48.47",
"7 10847555.07 396.43 -403.76 -34.83",
"8 5890470.68 397.09 -403.07 26.55",
"9 3198666.69 396.60 -403.58 -18.68",
"10 1736958.93 396.96 -403.20 14.65"
]
for out_line, exp_line in zip(output_lines, expected_lines):
self.assertEqual(out_line.rstrip(), exp_line)
def test_get_dataset(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
self.assertEqual(dataset.shape, (252, 16))
self.assertEqual(dataset[0][0], 12.6)
self.assertEqual(dataset[251][0], 30.7)
self.assertEqual(dataset[75][7], 91.6)
def test_compute_betas(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
betas = regression.compute_betas(dataset, [1, 2])
np.testing.assert_almost_equal(betas[0], 1.4029395600144443)
np.testing.assert_almost_equal(betas[1], 441.3525943592249)
np.testing.assert_almost_equal(betas[2], -400.5954953685588)
np.testing.assert_almost_equal(betas[3], 0.009892204826346139)
def test_gradient_descent(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
grad_desc = regression.gradient_descent(dataset,
cols=[2, 3],
betas=[0, 0, 0])
numpy.testing.assert_almost_equal(
grad_desc, np.array([-37.87698413, -1756.37222222,
-7055.35138889]))
def test_print_stats(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
capturedOutput = io.StringIO()
sys.stdout = capturedOutput
regression.print_stats(dataset, 1)
output = capturedOutput.getvalue()
sys.stdout = sys.__stdout__
self.assertEqual(output, "252\n1.06\n0.02\n")
def test_regression(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
mse = regression.regression(dataset, cols=[2, 3], betas=[0, 0, 0])
numpy.testing.assert_almost_equal(mse, 418.50384920634923, 7)
mse = regression.regression(dataset,
cols=[2, 3, 4],
betas=[0, -1.1, -.2, 3])
numpy.testing.assert_almost_equal(mse, 11859.17408611111, 7)
def test_sgd(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
capturedOutput = io.StringIO()
sys.stdout = capturedOutput
regression.sgd(dataset, cols=[2, 3], betas=[0, 0, 0], T=5, eta=1e-6)
output = capturedOutput.getvalue()
output_lines = output.split('\n')
sys.stdout = sys.__stdout__
expected_lines = [
"1 387.33 0.00 0.00 0.00", "2 379.60 0.00 0.00 0.01",
"3 335.99 0.00 0.00 0.01", "4 285.89 0.00 0.00 0.02",
"5 245.75 0.00 0.01 0.03"
]
for out_line, exp_line in zip(output_lines, expected_lines):
self.assertEqual(out_line.rstrip(), exp_line)
def test_predict(self):
dataset = regression.get_dataset(self.BODYFAT_FILE)
prediction = regression.predict(dataset,
cols=[1, 2],
features=[1.0708, 23])
np.testing.assert_almost_equal(prediction, 12.62245862957813)
