From d05db36366f0db3a1b07d8999ad9fe49d0bb0ce3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A1s=20Simon?= <simonandras97@gmail.com>
Date: Sun, 29 Aug 2021 00:07:45 +0200
Subject: [PATCH 01/19] Adding informative error message for the negative
 weight case (linear regression)

---
 sklearn/linear_model/_base.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/sklearn/linear_model/_base.py b/sklearn/linear_model/_base.py
index 79d6f321cb124..4c9651db2d3bf 100644
--- a/sklearn/linear_model/_base.py
+++ b/sklearn/linear_model/_base.py
@@ -664,6 +664,8 @@ def fit(self, X, y, sample_weight=None):
 
         if sample_weight is not None:
             sample_weight = _check_sample_weight(sample_weight, X, dtype=X.dtype)
+            if np.any(sample_weight < 0):
+                raise ValueError("The weights of the samples cannot be negative")
 
         X, y, X_offset, y_offset, X_scale = self._preprocess_data(
             X,

From 7370c51f3726e4021e850b1e00efbe1e2a325c4c Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Wed, 1 Sep 2021 20:03:50 +0200
Subject: [PATCH 02/19] The negativity check is now in _check_sample_weight
 which can be turned on with the only_positive bool parameter (beckward
 compatible). For the check the alredy written check_non_negative is used.

---
 sklearn/linear_model/_base.py | 6 ++----
 sklearn/utils/validation.py   | 5 ++++-
 2 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/sklearn/linear_model/_base.py b/sklearn/linear_model/_base.py
index 4c9651db2d3bf..5e707d5e9eba4 100644
--- a/sklearn/linear_model/_base.py
+++ b/sklearn/linear_model/_base.py
@@ -662,10 +662,8 @@ def fit(self, X, y, sample_weight=None):
             X, y, accept_sparse=accept_sparse, y_numeric=True, multi_output=True
         )
 
-        if sample_weight is not None:
-            sample_weight = _check_sample_weight(sample_weight, X, dtype=X.dtype)
-            if np.any(sample_weight < 0):
-                raise ValueError("The weights of the samples cannot be negative")
+        if sample_weight is not None:  # the weights should be non-negative
+            sample_weight = _check_sample_weight(sample_weight, X, only_positive=True, dtype=X.dtype)
 
         X, y, X_offset, y_offset, X_scale = self._preprocess_data(
             X,
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 871f4a191b2a9..104458c6d39a7 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1479,7 +1479,7 @@ def _check_psd_eigenvalues(lambdas, enable_warnings=False):
     return lambdas
 
 
-def _check_sample_weight(sample_weight, X, dtype=None, copy=False):
+def _check_sample_weight(sample_weight, X, only_positive=False, dtype=None, copy=False):
     """Validate sample weights.
 
     Note that passing sample_weight=None will output an array of ones.
@@ -1540,6 +1540,9 @@ def _check_sample_weight(sample_weight, X, dtype=None, copy=False):
                 )
             )
 
+    if only_positive:
+        check_non_negative(sample_weight, "sample weight")
+
     return sample_weight
 
 

From 8c07156de3a5b87c5bd8379287106ae725d3c46a Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Wed, 1 Sep 2021 20:25:50 +0200
Subject: [PATCH 03/19] Adding parameter documentation to the changed
 _check_sample_weight and rename the only_positive parameter to
 only_non_negative, because zeros are accepted.

---
 sklearn/linear_model/_base.py | 2 +-
 sklearn/utils/validation.py   | 6 ++++--
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/sklearn/linear_model/_base.py b/sklearn/linear_model/_base.py
index 5e707d5e9eba4..93fd2cb3e617c 100644
--- a/sklearn/linear_model/_base.py
+++ b/sklearn/linear_model/_base.py
@@ -663,7 +663,7 @@ def fit(self, X, y, sample_weight=None):
         )
 
         if sample_weight is not None:  # the weights should be non-negative
-            sample_weight = _check_sample_weight(sample_weight, X, only_positive=True, dtype=X.dtype)
+            sample_weight = _check_sample_weight(sample_weight, X, only_non_negative=True, dtype=X.dtype)
 
         X, y, X_offset, y_offset, X_scale = self._preprocess_data(
             X,
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 104458c6d39a7..5f1b8b407631a 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1479,7 +1479,7 @@ def _check_psd_eigenvalues(lambdas, enable_warnings=False):
     return lambdas
 
 
-def _check_sample_weight(sample_weight, X, only_positive=False, dtype=None, copy=False):
+def _check_sample_weight(sample_weight, X, only_non_negative=False, dtype=None, copy=False):
     """Validate sample weights.
 
     Note that passing sample_weight=None will output an array of ones.
@@ -1494,6 +1494,8 @@ def _check_sample_weight(sample_weight, X, only_positive=False, dtype=None, copy
 
     X : {ndarray, list, sparse matrix}
         Input data.
+        
+    only_non_negative : if True then a non negativity check for the sample_weight will be done
 
     dtype : dtype, default=None
        dtype of the validated `sample_weight`.
@@ -1540,7 +1542,7 @@ def _check_sample_weight(sample_weight, X, only_positive=False, dtype=None, copy
                 )
             )
 
-    if only_positive:
+    if only_non_negative:
         check_non_negative(sample_weight, "sample weight")
 
     return sample_weight

From f0583d96ead24fa6d305f26fec20fe9de196ce8b Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 02:00:33 +0200
Subject: [PATCH 04/19] Making some lines shorter than 88 char to pass tests

---
 sklearn/linear_model/_base.py | 4 +++-
 sklearn/utils/validation.py   | 3 ++-
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/sklearn/linear_model/_base.py b/sklearn/linear_model/_base.py
index 93fd2cb3e617c..6e1d6acb0cc91 100644
--- a/sklearn/linear_model/_base.py
+++ b/sklearn/linear_model/_base.py
@@ -663,7 +663,9 @@ def fit(self, X, y, sample_weight=None):
         )
 
         if sample_weight is not None:  # the weights should be non-negative
-            sample_weight = _check_sample_weight(sample_weight, X, only_non_negative=True, dtype=X.dtype)
+            sample_weight = _check_sample_weight(
+                sample_weight, X, only_non_negative=True, dtype=X.dtype
+            )
 
         X, y, X_offset, y_offset, X_scale = self._preprocess_data(
             X,
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 5f1b8b407631a..3d912e2fb24ce 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1479,7 +1479,8 @@ def _check_psd_eigenvalues(lambdas, enable_warnings=False):
     return lambdas
 
 
-def _check_sample_weight(sample_weight, X, only_non_negative=False, dtype=None, copy=False):
+def _check_sample_weight(sample_weight, X, only_non_negative=False, dtype=None,
+                         copy=False):
     """Validate sample weights.
 
     Note that passing sample_weight=None will output an array of ones.

From b3216f895c856ab9e9fa74301764f0ca59a8c16d Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 02:07:18 +0200
Subject: [PATCH 05/19] Make one line documentation in two lines to pass test
 (it was too long)

---
 sklearn/utils/validation.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 3d912e2fb24ce..6984722ceacaa 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1496,7 +1496,8 @@ def _check_sample_weight(sample_weight, X, only_non_negative=False, dtype=None,
     X : {ndarray, list, sparse matrix}
         Input data.
         
-    only_non_negative : if True then a non negativity check for the sample_weight will be done
+    only_non_negative : if True then a non negativity check for the sample_weight
+        will be done
 
     dtype : dtype, default=None
        dtype of the validated `sample_weight`.

From bc914dc72611efacdea21969d99ecbb09b49a33f Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 02:11:43 +0200
Subject: [PATCH 06/19] Delete whitespace in blank line

---
 sklearn/utils/validation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 6984722ceacaa..71a29d036faf2 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1495,7 +1495,7 @@ def _check_sample_weight(sample_weight, X, only_non_negative=False, dtype=None,
 
     X : {ndarray, list, sparse matrix}
         Input data.
-        
+
     only_non_negative : if True then a non negativity check for the sample_weight
         will be done
 

From 1cbdcb4fca819484f74e5d6e7f1f163354eccb44 Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 02:15:45 +0200
Subject: [PATCH 07/19] Add a dot to end of sentence (in modified function
 documentation)

---
 sklearn/utils/validation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 71a29d036faf2..75d5ca0b9f9ab 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1497,7 +1497,7 @@ def _check_sample_weight(sample_weight, X, only_non_negative=False, dtype=None,
         Input data.
 
     only_non_negative : if True then a non negativity check for the sample_weight
-        will be done
+        will be done.
 
     dtype : dtype, default=None
        dtype of the validated `sample_weight`.

From a0d6a70c90416b63cd2ec65823558aaa23a964df Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 02:23:01 +0200
Subject: [PATCH 08/19] formatting with black .

---
 sklearn/utils/validation.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 75d5ca0b9f9ab..554f821539dad 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1479,8 +1479,9 @@ def _check_psd_eigenvalues(lambdas, enable_warnings=False):
     return lambdas
 
 
-def _check_sample_weight(sample_weight, X, only_non_negative=False, dtype=None,
-                         copy=False):
+def _check_sample_weight(
+    sample_weight, X, only_non_negative=False, dtype=None, copy=False
+):
     """Validate sample weights.
 
     Note that passing sample_weight=None will output an array of ones.

From 622a1c7b05699feec65f78d6a040d0a58301ca3f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A1s=20Simon?=
 <36902722+simonandras@users.noreply.github.com>
Date: Thu, 2 Sep 2021 20:19:46 +0200
Subject: [PATCH 09/19] Update sklearn/utils/validation.py

update documentation

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
---
 sklearn/utils/validation.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 554f821539dad..d241693d43b54 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1497,8 +1497,10 @@ def _check_sample_weight(
     X : {ndarray, list, sparse matrix}
         Input data.
 
-    only_non_negative : if True then a non negativity check for the sample_weight
-        will be done.
+    only_non_negative : bool, default=False,
+        Whether or not the weights are expected to be non-negative.
+        
+        .. versionadded:: 1.0
 
     dtype : dtype, default=None
        dtype of the validated `sample_weight`.

From 72c05f98cb63a99e873fec65e5999a6fac9455f1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A1s=20Simon?=
 <36902722+simonandras@users.noreply.github.com>
Date: Thu, 2 Sep 2021 20:24:27 +0200
Subject: [PATCH 10/19] Update sklearn/linear_model/_base.py

delete unnecessary comment

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
---
 sklearn/linear_model/_base.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/linear_model/_base.py b/sklearn/linear_model/_base.py
index 6e1d6acb0cc91..514525a14a012 100644
--- a/sklearn/linear_model/_base.py
+++ b/sklearn/linear_model/_base.py
@@ -662,7 +662,7 @@ def fit(self, X, y, sample_weight=None):
             X, y, accept_sparse=accept_sparse, y_numeric=True, multi_output=True
         )
 
-        if sample_weight is not None:  # the weights should be non-negative
+        if sample_weight is not None:
             sample_weight = _check_sample_weight(
                 sample_weight, X, only_non_negative=True, dtype=X.dtype
             )

From fb01e063d1e52f426dde3af5ca266ba24c8605c3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A1s=20Simon?=
 <36902722+simonandras@users.noreply.github.com>
Date: Thu, 2 Sep 2021 20:25:30 +0200
Subject: [PATCH 11/19] Update sklearn/utils/validation.py

Add `...` to function name in the error message

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
---
 sklearn/utils/validation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index d241693d43b54..d8e9c87df4414 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1548,7 +1548,7 @@ def _check_sample_weight(
             )
 
     if only_non_negative:
-        check_non_negative(sample_weight, "sample weight")
+        check_non_negative(sample_weight, "`sample_weight`")
 
     return sample_weight
 

From da6c6fdce27d12aff5b56e19821efe9fcc5485c3 Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 20:52:03 +0200
Subject: [PATCH 12/19] Solve the previous problems

---
 sklearn/ensemble/_weight_boosting.py           | 8 ++++----
 sklearn/ensemble/tests/test_weight_boosting.py | 2 +-
 sklearn/neighbors/_kde.py                      | 4 +---
 sklearn/neighbors/tests/test_kde.py            | 2 +-
 sklearn/utils/validation.py                    | 8 ++++++--
 5 files changed, 13 insertions(+), 11 deletions(-)

diff --git a/sklearn/ensemble/_weight_boosting.py b/sklearn/ensemble/_weight_boosting.py
index 77ef449ba1933..a47937880d91c 100644
--- a/sklearn/ensemble/_weight_boosting.py
+++ b/sklearn/ensemble/_weight_boosting.py
@@ -123,10 +123,10 @@ def fit(self, X, y, sample_weight=None):
             y_numeric=is_regressor(self),
         )
 
-        sample_weight = _check_sample_weight(sample_weight, X, np.float64, copy=True)
+        sample_weight = _check_sample_weight(
+            sample_weight, X, np.float64, copy=True, only_non_negative=True
+        )
         sample_weight /= sample_weight.sum()
-        if np.any(sample_weight < 0):
-            raise ValueError("sample_weight cannot contain negative weights")
 
         # Check parameters
         self._validate_estimator()
@@ -136,7 +136,7 @@ def fit(self, X, y, sample_weight=None):
         self.estimator_weights_ = np.zeros(self.n_estimators, dtype=np.float64)
         self.estimator_errors_ = np.ones(self.n_estimators, dtype=np.float64)
 
-        # Initializion of the random number instance that will be used to
+        # Initialization of the random number instance that will be used to
         # generate a seed at each iteration
         random_state = check_random_state(self.random_state)
 
diff --git a/sklearn/ensemble/tests/test_weight_boosting.py b/sklearn/ensemble/tests/test_weight_boosting.py
index 6927d47c11cfe..159f83abf24c4 100755
--- a/sklearn/ensemble/tests/test_weight_boosting.py
+++ b/sklearn/ensemble/tests/test_weight_boosting.py
@@ -576,6 +576,6 @@ def test_adaboost_negative_weight_error(model, X, y):
     sample_weight = np.ones_like(y)
     sample_weight[-1] = -10
 
-    err_msg = "sample_weight cannot contain negative weight"
+    err_msg = "Negative values in data passed to `sample_weight`"
     with pytest.raises(ValueError, match=err_msg):
         model.fit(X, y, sample_weight=sample_weight)
diff --git a/sklearn/neighbors/_kde.py b/sklearn/neighbors/_kde.py
index 328a13371bafd..dcfc7b51f421a 100644
--- a/sklearn/neighbors/_kde.py
+++ b/sklearn/neighbors/_kde.py
@@ -191,9 +191,7 @@ def fit(self, X, y=None, sample_weight=None):
         X = self._validate_data(X, order="C", dtype=DTYPE)
 
         if sample_weight is not None:
-            sample_weight = _check_sample_weight(sample_weight, X, DTYPE)
-            if sample_weight.min() <= 0:
-                raise ValueError("sample_weight must have positive values")
+            sample_weight = _check_sample_weight(sample_weight, X, DTYPE, only_non_negative=True)
 
         kwargs = self.metric_params
         if kwargs is None:
diff --git a/sklearn/neighbors/tests/test_kde.py b/sklearn/neighbors/tests/test_kde.py
index 84f7623c8dbf1..d4fb775c44826 100644
--- a/sklearn/neighbors/tests/test_kde.py
+++ b/sklearn/neighbors/tests/test_kde.py
@@ -209,7 +209,7 @@ def test_sample_weight_invalid():
     data = np.reshape([1.0, 2.0, 3.0], (-1, 1))
 
     sample_weight = [0.1, -0.2, 0.3]
-    expected_err = "sample_weight must have positive values"
+    expected_err = "Negative values in data passed to `sample_weight`"
     with pytest.raises(ValueError, match=expected_err):
         kde.fit(data, sample_weight=sample_weight)
 
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index d8e9c87df4414..fbe58a3997d4b 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1480,7 +1480,11 @@ def _check_psd_eigenvalues(lambdas, enable_warnings=False):
 
 
 def _check_sample_weight(
-    sample_weight, X, only_non_negative=False, dtype=None, copy=False
+    sample_weight,
+    X,
+    dtype=None,
+    copy=False,
+    only_non_negative=False
 ):
     """Validate sample weights.
 
@@ -1499,7 +1503,7 @@ def _check_sample_weight(
 
     only_non_negative : bool, default=False,
         Whether or not the weights are expected to be non-negative.
-        
+
         .. versionadded:: 1.0
 
     dtype : dtype, default=None

From a7d5f2d4feb7883aee2460e85140c07d25977fc2 Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 20:55:43 +0200
Subject: [PATCH 13/19] reformatting with black .

---
 sklearn/neighbors/_kde.py   | 4 +++-
 sklearn/utils/validation.py | 6 +-----
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/sklearn/neighbors/_kde.py b/sklearn/neighbors/_kde.py
index dcfc7b51f421a..0ac0ea7226b90 100644
--- a/sklearn/neighbors/_kde.py
+++ b/sklearn/neighbors/_kde.py
@@ -191,7 +191,9 @@ def fit(self, X, y=None, sample_weight=None):
         X = self._validate_data(X, order="C", dtype=DTYPE)
 
         if sample_weight is not None:
-            sample_weight = _check_sample_weight(sample_weight, X, DTYPE, only_non_negative=True)
+            sample_weight = _check_sample_weight(
+                sample_weight, X, DTYPE, only_non_negative=True
+            )
 
         kwargs = self.metric_params
         if kwargs is None:
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index fbe58a3997d4b..4c75695419e17 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1480,11 +1480,7 @@ def _check_psd_eigenvalues(lambdas, enable_warnings=False):
 
 
 def _check_sample_weight(
-    sample_weight,
-    X,
-    dtype=None,
-    copy=False,
-    only_non_negative=False
+    sample_weight, X, dtype=None, copy=False, only_non_negative=False
 ):
     """Validate sample weights.
 

From b8741dbf1a71c1be8ce2f84fcc285573ebc28614 Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 21:16:07 +0200
Subject: [PATCH 14/19] In the documentation of _check_sample_weight changing
 the 3 space indents to 4 space indents

---
 sklearn/utils/validation.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
index 4c75695419e17..ab2faa373a034 100644
--- a/sklearn/utils/validation.py
+++ b/sklearn/utils/validation.py
@@ -1492,7 +1492,7 @@ def _check_sample_weight(
     Parameters
     ----------
     sample_weight : {ndarray, Number or None}, shape (n_samples,)
-       Input sample weights.
+        Input sample weights.
 
     X : {ndarray, list, sparse matrix}
         Input data.
@@ -1503,11 +1503,11 @@ def _check_sample_weight(
         .. versionadded:: 1.0
 
     dtype : dtype, default=None
-       dtype of the validated `sample_weight`.
-       If None, and the input `sample_weight` is an array, the dtype of the
-       input is preserved; otherwise an array with the default numpy dtype
-       is be allocated.  If `dtype` is not one of `float32`, `float64`,
-       `None`, the output will be of dtype `float64`.
+        dtype of the validated `sample_weight`.
+        If None, and the input `sample_weight` is an array, the dtype of the
+        input is preserved; otherwise an array with the default numpy dtype
+        is be allocated.  If `dtype` is not one of `float32`, `float64`,
+        `None`, the output will be of dtype `float64`.
 
     copy : bool, default=False
         If True, a copy of sample_weight will be created.
@@ -1515,7 +1515,7 @@ def _check_sample_weight(
     Returns
     -------
     sample_weight : ndarray of shape (n_samples,)
-       Validated sample weight. It is guaranteed to be "C" contiguous.
+        Validated sample weight. It is guaranteed to be "C" contiguous.
     """
     n_samples = _num_samples(X)
 

From ed20f5a186de33485282fc903476267e28730ac9 Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 23:37:16 +0200
Subject: [PATCH 15/19] Adding test to test_validation.py to test the negative
 weight error in the _check_sample_weigth function

---
 sklearn/utils/tests/test_validation.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index 45c24d696cd40..6ce2696920028 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -51,8 +51,8 @@
     _num_features,
     FLOAT_DTYPES,
     _get_feature_names,
+    _check_fit_params
 )
-from sklearn.utils.validation import _check_fit_params
 from sklearn.base import BaseEstimator
 import sklearn
 
@@ -1240,6 +1240,14 @@ def test_check_sample_weight():
     sample_weight = _check_sample_weight(None, X, dtype=X.dtype)
     assert sample_weight.dtype == np.float64
 
+    # check negative weight when only_non_negative=True
+    X = np.ones((5, 2))
+    sample_weight = np.ones(_num_samples(X))
+    sample_weight[-1] = -10
+    err_msg = "Negative values in data passed to `sample_weight`"
+    with pytest.raises(ValueError, match=err_msg):
+        _check_sample_weight(sample_weight, X, only_non_negative=True)
+
 
 @pytest.mark.parametrize("toarray", [np.array, sp.csr_matrix, sp.csc_matrix])
 def test_allclose_dense_sparse_equals(toarray):

From 9c24e51445fd96da78e46d3b9a67a11357ea0c5f Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Thu, 2 Sep 2021 23:42:40 +0200
Subject: [PATCH 16/19] black .

---
 sklearn/utils/tests/test_validation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
index 6ce2696920028..69a102f58acd7 100644
--- a/sklearn/utils/tests/test_validation.py
+++ b/sklearn/utils/tests/test_validation.py
@@ -51,7 +51,7 @@
     _num_features,
     FLOAT_DTYPES,
     _get_feature_names,
-    _check_fit_params
+    _check_fit_params,
 )
 from sklearn.base import BaseEstimator
 import sklearn

From 3acb9b36e805488267d91936d6cdf91baf46db91 Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Fri, 3 Sep 2021 00:35:08 +0200
Subject: [PATCH 17/19] In LinearRegression in fit method in
 _check_sample_weight function call make the parameter order like in the
 function definition

---
 sklearn/linear_model/_base.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/linear_model/_base.py b/sklearn/linear_model/_base.py
index 514525a14a012..8b5102ecdd403 100644
--- a/sklearn/linear_model/_base.py
+++ b/sklearn/linear_model/_base.py
@@ -664,7 +664,7 @@ def fit(self, X, y, sample_weight=None):
 
         if sample_weight is not None:
             sample_weight = _check_sample_weight(
-                sample_weight, X, only_non_negative=True, dtype=X.dtype
+                sample_weight, X, dtype=X.dtype, only_non_negative=True
             )
 
         X, y, X_offset, y_offset, X_scale = self._preprocess_data(

From 95ac8bfe5b67098b90fe5990247f8e522195f2a6 Mon Sep 17 00:00:00 2001
From: simonandras <simonandras97@gmail.com>
Date: Fri, 3 Sep 2021 13:47:46 +0200
Subject: [PATCH 18/19] Added entry to the changelog (sklearn.utils). Also
 corrected 2 typo in the changelog.

---
 doc/whats_new/v1.0.rst | 16 ++++++++++++++--
 1 file changed, 14 insertions(+), 2 deletions(-)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index 79f68c80df0ec..b2002d75728a0 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -821,7 +821,7 @@ Changelog
   unavailable on the basis of state, in a more readable way.
   :pr:`19948` by `Joel Nothman`_.
 
-_ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
+- |Enhancement| :func:`utils.validation.check_is_fitted` now uses
   ``__sklearn_is_fitted__`` if available, instead of checking for attributes ending with
   an underscore. This also makes :class:`Pipeline` and
   :class:`preprocessing.FunctionTransformer` pass
@@ -856,7 +856,7 @@ _ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
   warning was previously raised in resampling utilities and functions using
   those utilities (e.g. :func:`model_selection.train_test_split`,
   :func:`model_selection.cross_validate`,
-  :func:`model_seleection.cross_val_score`,
+  :func:`model_selection.cross_val_score`,
   :func:`model_selection.cross_val_predict`).
   :pr:`20673` by :user:`Joris Van den Bossche  <jorisvandenbossche>`.
 
@@ -865,6 +865,18 @@ _ |Enhancement| :func:`utils.validation.check_is_fitted` now uses
   `np.int64`).
   :pr:`20727` by `Guillaume Lemaitre`_.
 
+- |Enhancement| :func:`utils.validation._check_sample_weight` can perform a
+  non-negativity check on the sample weights. It can be turned on
+  using the only_non_negative bool parameter.
+  Estimators that check for non-negative weights are updated:
+  :func:`linear_model.LinearRegression` (here the previous
+  error message was misleading),
+  :func:`ensemble.AdaBoostClassifier`,
+  :func:`ensemble.AdaBoostRegressor`,
+  :func:`neighbors.KernelDensity`.
+  :pr:`20880` by :user:`Guillaume Lemaitre <glemaitre>`
+  and :user:`András Simon <simonandras>`.
+
 :mod:`sklearn.validation`
 .........................
 

From 6864e9bfbbc5daaaf43dd23e137c2d3beac54486 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <g.lemaitre58@gmail.com>
Date: Wed, 8 Sep 2021 11:14:22 +0200
Subject: [PATCH 19/19] move whats new version

---
 doc/whats_new/v1.0.rst | 14 +-------------
 doc/whats_new/v1.1.rst | 17 ++++++++++++++---
 2 files changed, 15 insertions(+), 16 deletions(-)

diff --git a/doc/whats_new/v1.0.rst b/doc/whats_new/v1.0.rst
index 38407888dbc47..e15c8ec5ff832 100644
--- a/doc/whats_new/v1.0.rst
+++ b/doc/whats_new/v1.0.rst
@@ -901,7 +901,7 @@ Changelog
   warning was previously raised in resampling utilities and functions using
   those utilities (e.g. :func:`model_selection.train_test_split`,
   :func:`model_selection.cross_validate`,
-  :func:`model_selection.cross_val_score`,
+  :func:`model_seleection.cross_val_score`,
   :func:`model_selection.cross_val_predict`).
   :pr:`20673` by :user:`Joris Van den Bossche  <jorisvandenbossche>`.
 
@@ -910,18 +910,6 @@ Changelog
   `np.int64`).
   :pr:`20727` by `Guillaume Lemaitre`_.
 
-- |Enhancement| :func:`utils.validation._check_sample_weight` can perform a
-  non-negativity check on the sample weights. It can be turned on
-  using the only_non_negative bool parameter.
-  Estimators that check for non-negative weights are updated:
-  :func:`linear_model.LinearRegression` (here the previous
-  error message was misleading),
-  :func:`ensemble.AdaBoostClassifier`,
-  :func:`ensemble.AdaBoostRegressor`,
-  :func:`neighbors.KernelDensity`.
-  :pr:`20880` by :user:`Guillaume Lemaitre <glemaitre>`
-  and :user:`András Simon <simonandras>`.
-
 - |API| :func:`utils._testing.assert_warns` and
   :func:`utils._testing.assert_warns_message` are deprecated in 1.0 and will
   be removed in 1.2. Used `pytest.warns` context manager instead. Note that
diff --git a/doc/whats_new/v1.1.rst b/doc/whats_new/v1.1.rst
index 1639b4b691c65..fba40e25a9e7e 100644
--- a/doc/whats_new/v1.1.rst
+++ b/doc/whats_new/v1.1.rst
@@ -38,9 +38,20 @@ Changelog
     :pr:`123456` by :user:`Joe Bloggs <joeongithub>`.
     where 123456 is the *pull request* number, not the issue number.
 
-
-:mod:`sklearn.decomposition`
-............................
+:mod:`sklearn.utils`
+....................
+
+- |Enhancement| :func:`utils.validation._check_sample_weight` can perform a
+  non-negativity check on the sample weights. It can be turned on
+  using the only_non_negative bool parameter.
+  Estimators that check for non-negative weights are updated:
+  :func:`linear_model.LinearRegression` (here the previous
+  error message was misleading),
+  :func:`ensemble.AdaBoostClassifier`,
+  :func:`ensemble.AdaBoostRegressor`,
+  :func:`neighbors.KernelDensity`.
+  :pr:`20880` by :user:`Guillaume Lemaitre <glemaitre>`
+  and :user:`András Simon <simonandras>`.
 
 
 Code and Documentation Contributors