def test_model_sampler(self):
importance = 4.0
N = 10000
expected_ones = N * self._get_prob(importance)
self._test_sampler(
ModelSampler(self.dataset, UNWEIGHTED, MockModel(importance)), N,
expected_ones)
def test_power_smoothing_sampler(self):
importance = 4.0
N = 10000
expected_ones = N * self._get_prob(importance**0.5)
self._test_sampler(
PowerSmoothingSampler(
ModelSampler(self.dataset, UNWEIGHTED, MockModel(importance))),
N, expected_ones)
def test_adaptive_additive_smoothing_sampler(self):
importance = 4.0
c = (self.prior * 4.0 + (1.0 - self.prior) * 1.0) / 2.
N = 10000
expected_ones = N * self._get_prob(importance + c, 1.0 + c)
self._test_sampler(
AdaptiveAdditiveSmoothingSampler(
ModelSampler(self.dataset, UNWEIGHTED, MockModel(importance))),
N, expected_ones)
def test_additive_smoothing_sampler(self):
importance = 4.0
c = 2.0
N = 10000
expected_ones = N * self._get_prob(importance + c, 1.0 + c)
self._test_sampler(
AdditiveSmoothingSampler(ModelSampler(self.dataset, UNWEIGHTED,
MockModel(importance)),
c=c), N, expected_ones)