From 4591039ebace6cf5a3f859a00f0212b072585285 Mon Sep 17 00:00:00 2001
From: Jiaming Yuan <jm.yuan@outlook.com>
Date: Tue, 11 Jun 2019 16:04:09 +0800
Subject: [PATCH] Remove remaining reg:linear. (#4544)

---
 include/xgboost/objective.h       |  2 +-
 python-package/xgboost/sklearn.py | 15 ++++++++-------
 tests/cli/machine.conf.in         |  2 +-
 3 files changed, 10 insertions(+), 9 deletions(-)

diff --git a/include/xgboost/objective.h b/include/xgboost/objective.h
index 900a16836..2d531fd1b 100644
--- a/include/xgboost/objective.h
+++ b/include/xgboost/objective.h
@@ -108,7 +108,7 @@ struct ObjFunctionReg
  *
  * \code
  * // example of registering a objective
- * XGBOOST_REGISTER_OBJECTIVE(LinearRegression, "reg:linear")
+ * XGBOOST_REGISTER_OBJECTIVE(LinearRegression, "reg:squarederror")
  * .describe("Linear regression objective")
  * .set_body([]() {
  *     return new RegLossObj(LossType::kLinearSquare);
diff --git a/python-package/xgboost/sklearn.py b/python-package/xgboost/sklearn.py
index b80a79fcf..dc1d73e3f 100644
--- a/python-package/xgboost/sklearn.py
+++ b/python-package/xgboost/sklearn.py
@@ -136,11 +136,12 @@ class XGBModel(XGBModelBase):
     """
 
     def __init__(self, max_depth=3, learning_rate=0.1, n_estimators=100,
-                 verbosity=1, silent=None, objective="reg:linear", booster='gbtree',
-                 n_jobs=1, nthread=None, gamma=0, min_child_weight=1,
-                 max_delta_step=0, subsample=1, colsample_bytree=1, colsample_bylevel=1,
-                 colsample_bynode=1, reg_alpha=0, reg_lambda=1, scale_pos_weight=1,
-                 base_score=0.5, random_state=0, seed=None, missing=None,
+                 verbosity=1, silent=None, objective="reg:squarederror",
+                 booster='gbtree', n_jobs=1, nthread=None, gamma=0,
+                 min_child_weight=1, max_delta_step=0, subsample=1,
+                 colsample_bytree=1, colsample_bylevel=1, colsample_bynode=1,
+                 reg_alpha=0, reg_lambda=1, scale_pos_weight=1, base_score=0.5,
+                 random_state=0, seed=None, missing=None,
                  importance_type="gain", **kwargs):
         if not SKLEARN_INSTALLED:
             raise XGBoostError('sklearn needs to be installed in order to use this module')
@@ -377,7 +378,7 @@ class XGBModel(XGBModelBase):
 
         if callable(self.objective):
             obj = _objective_decorator(self.objective)
-            params["objective"] = "reg:linear"
+            params["objective"] = "reg:squarederror"
         else:
             obj = None
 
@@ -928,7 +929,7 @@ class XGBRFRegressor(XGBRegressor):
 
     def __init__(self, max_depth=3, learning_rate=1, n_estimators=100,
                  verbosity=1, silent=None,
-                 objective="reg:linear", n_jobs=1, nthread=None, gamma=0,
+                 objective="reg:squarederror", n_jobs=1, nthread=None, gamma=0,
                  min_child_weight=1, max_delta_step=0, subsample=0.8, colsample_bytree=1,
                  colsample_bylevel=1, colsample_bynode=0.8, reg_alpha=0, reg_lambda=1,
                  scale_pos_weight=1, base_score=0.5, random_state=0, seed=None,
diff --git a/tests/cli/machine.conf.in b/tests/cli/machine.conf.in
index acac74f93..0f12bfddf 100644
--- a/tests/cli/machine.conf.in
+++ b/tests/cli/machine.conf.in
@@ -1,6 +1,6 @@
 # Originally an example in demo/regression/
 booster = gbtree
-objective = reg:linear
+objective = reg:squarederror
 eta = 1.0
 gamma = 1.0
 seed = 0