def draw(pretty: bool):
set_id, set_version = BINARY_CLASS_SETS[8] # Boston
iris_data = Dataset.from_openml(set_id, set_version)
Types = [LGBEnsemble, RandomForestEnsemble,
CatboostEnsemble, XGBoostEnsemble]
for Type in Types:
params = {
'n_estimators': 2,
'max_depth': 3
}
ensemble = Type(params)
ensemble.fit(iris_data)
draw_trees(ensemble.trees, pretty)
def prepare() -> (RandomForestEnsemble, Dataset):
data = Dataset.from_openml('splice')
rf = RandomForestEnsemble({'n_estimators': 5, 'max_depth': 4})
rf.fit(data)
return rf, data
