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)