def test_learn_train_predict_prob_LGBC():
inputer = Inputers(
description_filepath="../../descriptions/pre/inputers/otto_group.yaml")
dataset = inputer.transform()
y = dataset[inputer.target].values
X = dataset[dataset.columns.difference([inputer.target])]
learner = Learners(
description_filepath="../../descriptions/learners/LGBC.yaml")
learner.train(X, y, checkpoint="otto_group_LGBMC.ckp")
assert learner.predict(X).shape == (61878, )
def test_learn_train_predict_XGBC():
inputer = Inputers(
description_filepath="../../descriptions/pre/inputers/wine.yaml")
dataset = inputer.transform()
y = dataset[inputer.target].values
X = dataset[dataset.columns.difference([inputer.target])]
learner = Learners(
description_filepath="../../descriptions/learners/XGBC.yaml")
learner.train(X, y, checkpoint="LGBMClassifier.ckp")
assert learner.predict(X).shape == (178, )
def test_predict_LGBC_no_fit():
inputer = Inputers(description_filepath=
"../../descriptions/pre/inputers/pima-diabetes.yaml")
diabetes = inputer.transform()
learner = Learners(
description_filepath="../../descriptions/learners/LGBC.yaml")
# learner.train(
# diabetes, target=inputer.target, checkpoint="diabetesLGBMC.ckp"
# )
X = diabetes
X_train = X[X.columns.difference([inputer.target])]
with pytest.raises(PasoError):
assert learner.predict(X_train).shape == (768, 2)