def test_train_and_predict(self):
x = pd.DataFrame([[-1], [-5], [1], [5]])
y = pd.Series([0, 0, 1, 1])
model = ClassicalModel(2,
GradientBoostingClassifier,
clf_params={
"n_estimators": 1,
"max_depth": 1
})
model.train(x, y)
y_pred = pd.Series(model.predict(x))
self.assertTrue(y.equals(y_pred))
def test_score(self):
x = pd.DataFrame([[-1], [-5], [1], [5]])
y = pd.Series([0, 0, 1, 2])
model = ClassicalModel(2,
GradientBoostingClassifier,
clf_params={
"n_estimators": 1,
"max_depth": 1
},
label_mapper=lambda x: x > 0)
model.train(x, y)
score = model.score(x, y)
y_pred = pd.Series(model.predict(x))
self.assertTrue(y_pred.equals(pd.Series([False, False, True, True])))
self.assertEqual(score, 1)