def test_reg_cost_func_data2_3(self):
y = self.data2[:, -1:]
X = self.data2[:, :-1]
m, n = X.shape
intercept = ones((m, 1), dtype=float64)
X = append(intercept, X, axis=1)
theta = array([[-25.3], [32], [7.8]])
_lambda = 1000000
assert_allclose([[43514185803.375198]],
reg_cost_func(X, y, theta, _lambda),
rtol=0, atol=0.001)
def test_reg_cost_func_data1_3(self):
y = self.data1[:, -1:]
X = self.data1[:, :-1]
m, n = X.shape
intercept = ones((m, 1), dtype=float64)
X = append(intercept, X, axis=1)
theta = array([[-1], [2]])
_lambda = 750
assert_allclose([[69.706373]],
reg_cost_func(X, y, theta, _lambda),
rtol=0, atol=0.001)
def test_reg_cost_func_data2_2(self):
y = self.data2[:, -1:]
X = self.data2[:, :-1]
m, n = X.shape
intercept = ones((m, 1), dtype=float64)
X = append(intercept, X, axis=1)
theta = ones((n + 1, 1), dtype=float64)
_lambda = 1000000
assert_allclose([[64828218577.393623]],
reg_cost_func(X, y, theta, _lambda),
rtol=0, atol=0.001)
def test_reg_cost_func_data1_1(self):
y = self.data1[:, -1:]
X = self.data1[:, :-1]
m, n = X.shape
intercept = ones((m, 1), dtype=float64)
X = append(intercept, X, axis=1)
theta = ones((n + 1, 1), dtype=float64)
_lambda = 0
assert_allclose([[10.266]],
reg_cost_func(X, y, theta, _lambda),
rtol=0, atol=0.001)
def J(theta):
return reg_cost_func(X, y, theta, _lambda)