def test_to_sql(self, model, titanic_vd):
model_test = DecisionTreeClassifier("rfc_sql_test")
model_test.drop()
model_test.fit(titanic_vd, ["age", "fare", "sex"], "survived")
current_cursor().execute(
"SELECT PREDICT_RF_CLASSIFIER(* USING PARAMETERS model_name = 'rfc_sql_test', match_by_pos=True)::int, {}::int FROM (SELECT 30.0 AS age, 45.0 AS fare, 'male' AS sex) x"
.format(model_test.to_sql()))
prediction = current_cursor().fetchone()
assert prediction[0] == prediction[1]
model_test.drop()
def test_contour(self, base, titanic_vd):
model_test = DecisionTreeClassifier("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_model_from_vDF(self, base, dtc_data_vd):
base.cursor.execute("DROP MODEL IF EXISTS tc_from_vDF")
model_test = DecisionTreeClassifier("tc_from_vDF", cursor=base.cursor)
model_test.fit(dtc_data_vd,
["Gender", '"owned cars"', "cost", "income"],
"TransPortation")
base.cursor.execute(
"SELECT model_name FROM models WHERE model_name = 'tc_from_vDF'")
assert base.cursor.fetchone()[0] == "tc_from_vDF"
model_test.drop()
def test_to_sql(self, model, titanic_vd):
model_test = DecisionTreeClassifier("rfc_sql_test", cursor=model.cursor)
model_test.drop()
model_test.fit(titanic_vd, ["age", "fare", "sex"], "survived")
model.cursor.execute(
"SELECT PREDICT_RF_CLASSIFIER(* USING PARAMETERS model_name = 'rfc_sql_test', match_by_pos=True, class=1, type='probability')::float, {}::float FROM (SELECT 30.0 AS age, 45.0 AS fare, 'male' AS sex) x".format(
model_test.to_sql()
)
)
prediction = model.cursor.fetchone()
assert prediction[0] == pytest.approx(prediction[1], 1e-2)
model_test.drop()
def test_to_python(self, model, titanic_vd):
model_test = DecisionTreeClassifier("rfc_python_test", cursor=model.cursor)
model_test.drop()
model_test.fit(titanic_vd, ["age", "fare", "sex"], "embarked")
model_test.cursor.execute(
"SELECT PREDICT_RF_CLASSIFIER(30.0, 45.0, 'male' USING PARAMETERS model_name = 'rfc_python_test', match_by_pos=True)"
)
prediction = model_test.cursor.fetchone()[0]
assert prediction == model_test.to_python(return_str=False)([[30.0, 45.0, 'male']])[0]
model_test.cursor.execute(
"SELECT PREDICT_RF_CLASSIFIER(30.0, 145.0, 'female' USING PARAMETERS model_name = 'rfc_python_test', match_by_pos=True)"
)
prediction = model_test.cursor.fetchone()[0]
assert prediction == model_test.to_python(return_str=False)([[30.0, 145.0, 'female']])[0]
def test_drop(self, base):
base.cursor.execute("DROP MODEL IF EXISTS decision_tc_model_test_drop")
model_test = DecisionTreeClassifier("decision_tc_model_test_drop",
cursor=base.cursor)
model_test.fit(
"public.dtc_data",
["Gender", '"owned cars"', "cost", "income"],
"TransPortation",
)
base.cursor.execute(
"SELECT model_name FROM models WHERE model_name = 'decision_tc_model_test_drop'"
)
assert base.cursor.fetchone()[0] == "decision_tc_model_test_drop"
model_test.drop()
base.cursor.execute(
"SELECT model_name FROM models WHERE model_name = 'decision_tc_model_test_drop'"
)
assert base.cursor.fetchone() is None