Deprecate LabelEncoder in XGBClassifier; Enable cuDF/cuPy inputs in XGBClassifier (#6269)

* Deprecate LabelEncoder in XGBClassifier; skip LabelEncoder for cuDF/cuPy inputs

* Add unit tests for cuDF and cuPy inputs with XGBClassifier

* Fix lint

* Clarify warning

* Move use_label_encoder option to XGBClassifier constructor

* Add a test for cudf.Series

* Add use_label_encoder to XGBRFClassifier doc

* Address reviewer feedback
This commit is contained in:
Philip Hyunsu Cho
2020-10-26 13:20:51 -07:00
committed by GitHub
parent bcfab4d726
commit c8ec62103a
4 changed files with 119 additions and 25 deletions

View File

@@ -172,6 +172,34 @@ Arrow specification.'''
_test_cudf_metainfo(xgb.DeviceQuantileDMatrix)
@pytest.mark.skipif(**tm.no_cudf())
@pytest.mark.skipif(**tm.no_cupy())
@pytest.mark.skipif(**tm.no_sklearn())
@pytest.mark.skipif(**tm.no_pandas())
def test_cudf_training_with_sklearn():
from cudf import DataFrame as df
from cudf import Series as ss
import pandas as pd
np.random.seed(1)
X = pd.DataFrame(np.random.randn(50, 10))
y = pd.DataFrame((np.random.randn(50) > 0).astype(np.int8))
weights = np.random.random(50) + 1.0
cudf_weights = df.from_pandas(pd.DataFrame(weights))
base_margin = np.random.random(50)
cudf_base_margin = df.from_pandas(pd.DataFrame(base_margin))
X_cudf = df.from_pandas(X)
y_cudf = df.from_pandas(y)
y_cudf_series = ss(data=y.iloc[:, 0])
for y_obj in [y_cudf, y_cudf_series]:
clf = xgb.XGBClassifier(gpu_id=0, tree_method='gpu_hist', use_label_encoder=False)
clf.fit(X_cudf, y_obj, sample_weight=cudf_weights, base_margin=cudf_base_margin,
eval_set=[(X_cudf, y_obj)])
pred = clf.predict(X_cudf)
assert np.array_equal(np.unique(pred), np.array([0, 1]))
class IterForDMatrixTest(xgb.core.DataIter):
'''A data iterator for XGBoost DMatrix.