def test_xgb_trainer_equal_classifier(self):
model1 = XGBClassifier(n_estimators=100,
learning_rate=0.1,
max_depth=3,
features=self.features,
random_state=42)
model2 = XGBTrainer(features=self.features,
objective='reg:logistic',
booster='gbtree',
tree_method='exact',
n_estimators=100,
learning_rate=0.1,
max_depth=3,
random_state=42)
y = np.where(self.y > 0, 1, 0)
model1.fit(self.x, y)
model2.fit(self.x, y)
predict1 = model1.predict(self.sample_x)
predict2 = model2.predict(self.sample_x)
predict2 = np.where(predict2 > 0.5, 1., 0.)
np.testing.assert_array_almost_equal(predict1, predict2)
def test_xgb_trainer_persistence(self):
model = XGBTrainer(features=self.features,
objective='binary:logistic',
booster='gbtree',
tree_method='hist',
n_estimators=200)
y = np.where(self.y > 0, 1, 0)
model.fit(self.x, y)
desc = model.save()
new_model = load_model(desc)
self.assertEqual(model.features, new_model.features)
np.testing.assert_array_almost_equal(model.predict(self.sample_x),
new_model.predict(self.sample_x))
np.testing.assert_array_almost_equal(model.importances,
new_model.importances)