Rearrange the parameters to avoid breaking changes.

python-package/xgboost/core.py

@@ -443,14 +443,14 @@ def __init__(
         self,
         data,
         label=None,
-        *,
         weight=None,
         base_margin=None,
+        missing: Optional[float] = None,
+        *,
         group=None,
         qid=None,
         label_lower_bound=None,
         label_upper_bound=None,
-        missing: Optional[float] = None,
         silent: bool = False,
         feature_weights=None,
         feature_names=None,
@@ -995,14 +995,14 @@ def __init__(              # pylint: disable=super-init-not-called
         self,
         data,
         label=None,
-        *,
         weight=None,
         base_margin=None,
+        missing=None,
+        *,
         group=None,
         qid=None,
         label_lower_bound=None,
         label_upper_bound=None,
-        missing=None,
         silent=False,
         feature_weights=None,
         feature_names=None,

python-package/xgboost/dask.py

@@ -202,13 +202,13 @@ class DaskDMatrix:
         data source of DMatrix.
     label :
         label used for trainin.
-    missing :
-        Value in the input data (e.g. `numpy.ndarray`) which needs to be present as a
-        missing value. If None, defaults to np.nan.
     weight :
         Weight for each instance.
     base_margin :
         Global bias for each instance.
+    missing :
+        Value in the input data (e.g. `numpy.ndarray`) which needs to be present as a
+        missing value. If None, defaults to np.nan.
     qid :
         Query ID for ranking.
     label_lower_bound :
@@ -221,7 +221,8 @@ class DaskDMatrix:
         Set names for features.
     feature_types :
         Set types for features
-
+    enable_categorical :
+        Enable categorical feature types, not yet supported on dask.
     '''
 
     @_deprecate_positional_args
@@ -230,14 +231,14 @@ def __init__(
         client: "distributed.Client",
         data: _DaskCollection,
         label: Optional[_DaskCollection] = None,
-        *,
         weight: Optional[_DaskCollection] = None,
         base_margin: Optional[_DaskCollection] = None,
+        missing: float = None,
+        *,
         group: Optional[_DaskCollection] = None,
         qid: Optional[_DaskCollection] = None,
         label_lower_bound: Optional[_DaskCollection] = None,
         label_upper_bound: Optional[_DaskCollection] = None,
-        missing: float = None,
         silent: bool = False,   # pylint: disable=unused-argument
         feature_weights: Optional[_DaskCollection] = None,
         feature_names: Optional[Union[str, List[str]]] = None,
@@ -605,14 +606,14 @@ def __init__(
         client: "distributed.Client",
         data: _DaskCollection,
         label: Optional[_DaskCollection] = None,
-        *,
         weight: Optional[_DaskCollection] = None,
         base_margin: Optional[_DaskCollection] = None,
+        missing: float = None,
+        *,
         group: Optional[_DaskCollection] = None,
         qid: Optional[_DaskCollection] = None,
         label_lower_bound: Optional[_DaskCollection] = None,
         label_upper_bound: Optional[_DaskCollection] = None,
-        missing: float = None,
         silent: bool = False,
         feature_weights: Optional[_DaskCollection] = None,
         feature_names: Optional[Union[str, List[str]]] = None,

python-package/xgboost/sklearn.py

@@ -931,10 +931,22 @@ def __init__(self, *, objective="binary:logistic", use_label_encoder=True, **kwa
         super().__init__(objective=objective, **kwargs)
 
     @_deprecate_positional_args
-    def fit(self, X, y, *, sample_weight=None, base_margin=None,
-            eval_set=None, eval_metric=None,
-            early_stopping_rounds=None, verbose=True, xgb_model=None,
-            sample_weight_eval_set=None, feature_weights=None, callbacks=None):
+    def fit(
+        self,
+        X,
+        y,
+        *,
+        sample_weight=None,
+        base_margin=None,
+        eval_set=None,
+        eval_metric=None,
+        early_stopping_rounds=None,
+        verbose=True,
+        xgb_model=None,
+        sample_weight_eval_set=None,
+        feature_weights=None,
+        callbacks=None
+    ):
         # pylint: disable = attribute-defined-outside-init,arguments-differ,too-many-statements
 
         can_use_label_encoder = True
@@ -1303,7 +1315,8 @@ def __init__(self, *, objective='rank:pairwise', **kwargs):
     def fit(
         self,
         X,
-        y, *,
+        y,
+        *,
         group=None,
         qid=None,
         sample_weight=None,