def test_get_plot(self, winequality_vd):
current_cursor().execute("DROP MODEL IF EXISTS model_test_plot")
model_test = XGBoostRegressor("model_test_plot", )
model_test.fit(winequality_vd, ["alcohol"], "quality")
result = model_test.plot()
assert len(result.get_default_bbox_extra_artists()) in (9, 12)
plt.close("all")
model_test.drop()
def test_get_plot(self, base, winequality_vd):
base.cursor.execute("DROP MODEL IF EXISTS model_test_plot")
model_test = XGBoostRegressor("model_test_plot", cursor=base.cursor)
model_test.fit(winequality_vd, ["alcohol"], "quality")
result = model_test.plot()
assert len(result.get_default_bbox_extra_artists()) == 9
plt.close("all")
model_test.drop()
def test_model_from_vDF(self, xgbr_data_vd):
current_cursor().execute("DROP MODEL IF EXISTS xgbr_from_vDF")
model_test = XGBoostRegressor("xgbr_from_vDF", )
model_test.fit(xgbr_data_vd, ["gender"], "transportation")
current_cursor().execute(
"SELECT model_name FROM models WHERE model_name = 'xgbr_from_vDF'")
assert current_cursor().fetchone()[0] == "xgbr_from_vDF"
model_test.drop()
def test_contour(self, titanic_vd):
model_test = XGBoostRegressor("model_contour", )
model_test.drop()
model_test.fit(
titanic_vd,
["age", "fare"],
"survived",
)
result = model_test.contour()
assert len(result.get_default_bbox_extra_artists()) in (37, 34)
model_test.drop()
def test_contour(self, base, titanic_vd):
model_test = XGBoostRegressor("model_contour", cursor=base.cursor)
model_test.drop()
model_test.fit(
titanic_vd,
[
"age",
"fare",
],
"survived",
)
result = model_test.contour()
assert len(result.get_default_bbox_extra_artists()) == 34
model_test.drop()
def test_drop(self):
current_cursor().execute("DROP MODEL IF EXISTS xgbr_model_test_drop")
model_test = XGBoostRegressor("xgbr_model_test_drop", )
model_test.fit(
"public.xgbr_data",
['"Gender"', '"owned cars"', '"cost"', '"income"'],
"TransPortation",
)
current_cursor().execute(
"SELECT model_name FROM models WHERE model_name = 'xgbr_model_test_drop'"
)
assert current_cursor().fetchone()[0] == "xgbr_model_test_drop"
model_test.drop()
current_cursor().execute(
"SELECT model_name FROM models WHERE model_name = 'xgbr_model_test_drop'"
)
assert current_cursor().fetchone() is None
def test_to_json(self, titanic_vd):
titanic = titanic_vd.copy()
titanic.fillna()
path = "verticapy_test_xgbr.json"
X = ["pclass", "age", "survived"]
y = "fare"
model = XGBoostRegressor("verticapy_xgb_regressor_test",
max_ntree=10,
max_depth=5)
model.drop()
model.fit(titanic, X, y)
X_test = titanic[X].to_numpy()
y_test_vertica = model.to_python()(X_test)
if os.path.exists(path):
os.remove(path)
model.to_json(path)
model_python = xgb.XGBRegressor()
model_python.load_model(path)
y_test_python = model_python.predict(X_test)
result = (y_test_vertica - y_test_python)**2
result = result.sum() / len(result)
assert result == pytest.approx(0.0, abs=1.0e-11)
model.drop()
os.remove(path)