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:
Jiaming Yuan
2019-09-16 23:52:00 -04:00
committed by GitHub
parent 125bcec62e
commit 5374f52531
17 changed files with 702 additions and 339 deletions

View File

@@ -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)