def test_best_combination(self):
isis = ISIS(SIS(gamma=0.5, selector=L0BrutalForce(1e-4)),
l0_regulate=False)
_ = isis.run(self.x.values, self.y, max_p=4)
comb_best, coeff_best, score_best = _best_combination(
self.x.values, self.y, np.array([10, 11]), np.array([12, 0]))
self.assertArrayEqual(comb_best, [10, 11, 12])
self.assertArrayAlmostEqual(coeff_best, [1, 1, 1])
self.assertAlmostEqual(score_best, 0)
def test_isis(self):
# isis = ISIS(SIS(gamma=0.5, selector=L0BrutalForce(1e-4)))
# selected = isis.run(self.x.values, self.y, max_p=4)
# # np.testing.assert_equal(selected, [10, 11, 12, 4, 5, 6, 0, 3, 2, 8])
# np.testing.assert_equal(selected, [10, 11, 12, 4])
# Test update gamma
isis = ISIS(SIS(gamma=0.1, selector=L0BrutalForce(1e-4)))
selected = isis.run(self.x.values, self.y, max_p=5)
self.assertAlmostEqual(isis.sis.gamma, 0.15)
# # np.testing.assert_equal(selected, [10, 11, 12, 4, 5, 6, 0, 3, 2, 8])
np.testing.assert_equal(selected, [10, 11, 12, 5, 0])
def test_evaluate(self):
isis = ISIS(SIS(gamma=0.5, selector=L0BrutalForce(1e-4)),
l0_regulate=False)
_ = isis.run(self.x.values, self.y, max_p=4)
mae = isis.evaluate(self.x.values, self.y)
self.assertAlmostEqual(mae, 0)
def test_coeff(self):
isis = ISIS(SIS(gamma=0.5, selector=L0BrutalForce(1e-4)))
coeff = _get_coeff(self.x.values, self.y)
self.assertArrayAlmostEqual(coeff[10:], [1, 1, 1])