def test_combo_mpg(mpg_data): hb_mpg = combo_manip_mpg(mpg_data) targets = hb_mpg["mpg"].values col_names = hb_mpg.columns.values data = hb_mpg[col_names[1:]].values message = "Running Combo Binary and Label encodings" run_model(data, targets, message, regression=True)
def test_one_hot(mpg_data): hb_mpg = one_hot_mpg(mpg_data) targets = hb_mpg["mpg"].values col_names = hb_mpg.columns.values data = hb_mpg[col_names[1:]].values message = "Running one hot" run_model(data, targets, message, regression=True)
def test_label_encoding(cars_data): fr_cars = label_encode_car(cars_data) targets = fr_cars["target"].values column_names = fr_cars.columns.values data = fr_cars[column_names[:-1]].values message = "Running label encoding" run_model(data, targets, message)
def test_label_encoding(ds): """ Test's :param ds: :return: """ hb_math = label_encode_math(ds) targets = hb_math["G3"].values col_names = hb_math.columns.values data = hb_math[col_names[1:]].values message = "Running label encoding on math dataset" run_model(data, targets, message, regression=True)
def test_one_hot(dataset): """ Tests the dataset with one hot encoding on category columns :param dataset: :return: """ hb_math = one_hot_math(dataset) hb_math = replace_yes_no(hb_math) targets = hb_math["G3"].values col_names = hb_math.columns.values data = hb_math[col_names[1:]].values message = "running one hot on student math" run_model(data, targets, message, regression=True)
def test_one_hot(cars_data): hb_cars = one_hot_car(cars_data) clean_up_targets = { "target": { "unacc": 0, "acc": 1, "good": 2, "vgood": 3 } } hb_cars.replace(clean_up_targets, inplace=True) targets = hb_cars["target"].values column_names = hb_cars.columns.values data = hb_cars[column_names[1:]].values message = "Running one hot" run_model(data, targets, message)