Complete cudf support. (#4850)
* Handles missing value. * Accept all floating point and integer types. * Move to cudf 9.0 API. * Remove requirement on `null_count`. * Arbitrary column types support.
This commit is contained in:
@@ -69,8 +69,8 @@ class TestUpdaters(unittest.TestCase):
|
||||
nan = np.nan
|
||||
param = {'missing': nan, 'tree_method': 'hist'}
|
||||
model = xgb.XGBRegressor(**param)
|
||||
X = [[6.18827160e+05, 1.73000000e+02], [6.37345679e+05, nan],
|
||||
[6.38888889e+05, nan], [6.28086420e+05, nan]]
|
||||
X = np.array([[6.18827160e+05, 1.73000000e+02], [6.37345679e+05, nan],
|
||||
[6.38888889e+05, nan], [6.28086420e+05, nan]])
|
||||
y = [1000000., 0., 0., 500000.]
|
||||
w = [0, 0, 1, 0]
|
||||
model.fit(X, y, sample_weight=w)
|
||||
|
||||
Reference in New Issue
Block a user