def test_numerical_default_transform():
optb = ContinuousOptimalBinning()
with raises(NotFittedError):
x_transform = optb.transform(x)
optb.fit(x, y)
x_transform = optb.transform([0.2, 4.1, 7.2, 26])
assert x_transform == approx([39.718, 39.718, 25.56067416, 11.82978723],
rel=1e-6)
def test_default_transform_continuous():
data = load_boston()
variable_names = data.feature_names
X = data.data
y = data.target
process = BinningProcess(variable_names)
process.fit(X, y)
X_transform = process.transform(X)
optb = process.get_binned_variable(variable_names[0])
assert isinstance(optb, ContinuousOptimalBinning)
optb = ContinuousOptimalBinning()
x = X[:, 5]
optb.fit(x, y)
assert optb.transform(x) == approx(X_transform[:, 5], rel=1e-6)