From e40258f507ea6bcf6b059f5017367dbe7cb7c4ac Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 1 Oct 2018 16:04:10 +0530
Subject: [PATCH 01/23] Add max error metric

---
 sklearn/metrics/regression.py | 37 ++++++++++++++++++++++++++++++++++-
 1 file changed, 36 insertions(+), 1 deletion(-)

diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
index e9084a4276e18..1da51443fc5b6 100644
--- a/sklearn/metrics/regression.py
+++ b/sklearn/metrics/regression.py
@@ -36,7 +36,8 @@
     "mean_squared_log_error",
     "median_absolute_error",
     "r2_score",
-    "explained_variance_score"
+    "explained_variance_score",
+    "max_error"
 ]
 
 
@@ -573,3 +574,37 @@ def r2_score(y_true, y_pred, sample_weight=None,
         avg_weights = multioutput
 
     return np.average(output_scores, weights=avg_weights)
+
+
+def max_error(y_true, y_pred):
+    """
+    The Max-Error metric is the worst case error
+    between the predicted value and the true value.
+
+    Parameters
+    ----------
+    y_true : array-like of shape = (n_samples)
+        Ground truth (correct) target values.
+
+    y_pred : array-like of shape = (n_samples)
+        Estimated target values.
+
+    Returns
+    -------
+    max_error : float
+        A positive floating point value (the best value is 0.0).
+
+    Examples
+    --------
+    >>> from sklearn.metrics import max_error
+    >>> y_true = [3.1, 2.4, 7.6, 1.9]
+    >>> y_pred = [4.1, 2.3, 7.4, 1.7]
+    >>> median_absolute_error(y_true, y_pred)
+    1.0
+    """
+    y_type, y_true, y_pred, _ = _check_reg_targets(y_true, y_pred,
+                                                   'uniform_average')
+    if y_type == 'continuous-multioutput':
+        raise ValueError("Multioutput not supported in max_error")
+    max_error = np.around(np.max(np.abs(y_true - y_pred)), decimals=3)
+    return max_error

From 6905ee40c30b3186af8c36e108866b33e76f56f1 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 1 Oct 2018 16:09:28 +0530
Subject: [PATCH 02/23] Fix typo

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

diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
index 1da51443fc5b6..bce878dc306fc 100644
--- a/sklearn/metrics/regression.py
+++ b/sklearn/metrics/regression.py
@@ -599,7 +599,7 @@ def max_error(y_true, y_pred):
     >>> from sklearn.metrics import max_error
     >>> y_true = [3.1, 2.4, 7.6, 1.9]
     >>> y_pred = [4.1, 2.3, 7.4, 1.7]
-    >>> median_absolute_error(y_true, y_pred)
+    >>> max_error(y_true, y_pred)
     1.0
     """
     y_type, y_true, y_pred, _ = _check_reg_targets(y_true, y_pred,

From 0e92ee3858da0217a3d5812cf7226ccbf6ce91b5 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 1 Oct 2018 17:57:32 +0530
Subject: [PATCH 03/23] Fix some imports

---
 sklearn/metrics/__init__.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/sklearn/metrics/__init__.py b/sklearn/metrics/__init__.py
index 2d19e24db8683..5f0c5cd293115 100644
--- a/sklearn/metrics/__init__.py
+++ b/sklearn/metrics/__init__.py
@@ -60,6 +60,7 @@
 from .regression import mean_squared_log_error
 from .regression import median_absolute_error
 from .regression import r2_score
+from .regression import max_error
 
 from .scorer import check_scoring
 from .scorer import make_scorer
@@ -99,6 +100,7 @@
     'log_loss',
     'make_scorer',
     'matthews_corrcoef',
+    'max_error',
     'mean_absolute_error',
     'mean_squared_error',
     'mean_squared_log_error',

From 06f14d8a0bf7de0ae554fe58a6e9e746b436a3a1 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 1 Oct 2018 18:43:24 +0530
Subject: [PATCH 04/23] Adding some test for max error

---
 sklearn/metrics/tests/test_regression.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/sklearn/metrics/tests/test_regression.py b/sklearn/metrics/tests/test_regression.py
index 2faaaad3a39f2..86849bd159358 100644
--- a/sklearn/metrics/tests/test_regression.py
+++ b/sklearn/metrics/tests/test_regression.py
@@ -14,6 +14,7 @@
 from sklearn.metrics import mean_squared_error
 from sklearn.metrics import mean_squared_log_error
 from sklearn.metrics import median_absolute_error
+from sklearn.metrics import max_error
 from sklearn.metrics import r2_score
 
 from sklearn.metrics.regression import _check_reg_targets
@@ -29,6 +30,7 @@ def test_regression_metrics(n_samples=50):
                                            np.log(1 + y_pred)))
     assert_almost_equal(mean_absolute_error(y_true, y_pred), 1.)
     assert_almost_equal(median_absolute_error(y_true, y_pred), 1.)
+    assert_almost_equal(max_error(y_true, y_pred), 1.)
     assert_almost_equal(r2_score(y_true, y_pred),  0.995, 2)
     assert_almost_equal(explained_variance_score(y_true, y_pred), 1.)
 
@@ -59,6 +61,7 @@ def test_regression_metrics_at_limits():
     assert_almost_equal(mean_squared_log_error([0.], [0.]), 0.00, 2)
     assert_almost_equal(mean_absolute_error([0.], [0.]), 0.00, 2)
     assert_almost_equal(median_absolute_error([0.], [0.]), 0.00, 2)
+    assert_almost_equal(max_error([0.], [0.]), 0.00, 2)
     assert_almost_equal(explained_variance_score([0.], [0.]), 1.00, 2)
     assert_almost_equal(r2_score([0., 1], [0., 1]), 1.00, 2)
     assert_raises_regex(ValueError, "Mean Squared Logarithmic Error cannot be "

From ea9d3f07f4916b4179903dbe7afd48d65ed81bd9 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 1 Oct 2018 19:04:29 +0530
Subject: [PATCH 05/23] Add scorer for max error

---
 sklearn/metrics/scorer.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/sklearn/metrics/scorer.py b/sklearn/metrics/scorer.py
index 2661a379b4e53..84e5daa4f2307 100644
--- a/sklearn/metrics/scorer.py
+++ b/sklearn/metrics/scorer.py
@@ -22,7 +22,7 @@
 
 import numpy as np
 
-from . import (r2_score, median_absolute_error, mean_absolute_error,
+from . import (r2_score, median_absolute_error, max_error, mean_absolute_error,
                mean_squared_error, mean_squared_log_error, accuracy_score,
                f1_score, roc_auc_score, average_precision_score,
                precision_score, recall_score, log_loss,
@@ -454,6 +454,7 @@ def make_scorer(score_func, greater_is_better=True, needs_proba=False,
 # Standard regression scores
 explained_variance_scorer = make_scorer(explained_variance_score)
 r2_scorer = make_scorer(r2_score)
+max_error_scorer = make_scorer(max_error)
 neg_mean_squared_error_scorer = make_scorer(mean_squared_error,
                                             greater_is_better=False)
 neg_mean_squared_log_error_scorer = make_scorer(mean_squared_log_error,
@@ -498,6 +499,7 @@ def make_scorer(score_func, greater_is_better=True, needs_proba=False,
 
 SCORERS = dict(explained_variance=explained_variance_scorer,
                r2=r2_scorer,
+               max_error=max_error_scorer,
                neg_median_absolute_error=neg_median_absolute_error_scorer,
                neg_mean_absolute_error=neg_mean_absolute_error_scorer,
                neg_mean_squared_error=neg_mean_squared_error_scorer,

From 7b8222f456dc42530f5f6243823f607317e62302 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Wed, 3 Oct 2018 14:20:21 +0530
Subject: [PATCH 06/23] Add max_error_scorer to fix the failing test

---
 sklearn/metrics/tests/test_score_objects.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/sklearn/metrics/tests/test_score_objects.py b/sklearn/metrics/tests/test_score_objects.py
index da04b4215dce0..85360151a1655 100644
--- a/sklearn/metrics/tests/test_score_objects.py
+++ b/sklearn/metrics/tests/test_score_objects.py
@@ -47,7 +47,8 @@
                       'neg_mean_absolute_error', 'neg_mean_squared_error',
                       'neg_mean_squared_log_error',
                       'neg_median_absolute_error', 'mean_absolute_error',
-                      'mean_squared_error', 'median_absolute_error']
+                      'mean_squared_error', 'median_absolute_error',
+                      'max_error_scorer']
 
 CLF_SCORERS = ['accuracy', 'balanced_accuracy',
                'f1', 'f1_weighted', 'f1_macro', 'f1_micro',

From 237759afaaa2bd4930175bf9245b6018651209c4 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Wed, 3 Oct 2018 15:11:19 +0530
Subject: [PATCH 07/23] correct typo in scorer name

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

diff --git a/sklearn/metrics/tests/test_score_objects.py b/sklearn/metrics/tests/test_score_objects.py
index 85360151a1655..633caf9a9b339 100644
--- a/sklearn/metrics/tests/test_score_objects.py
+++ b/sklearn/metrics/tests/test_score_objects.py
@@ -48,7 +48,7 @@
                       'neg_mean_squared_log_error',
                       'neg_median_absolute_error', 'mean_absolute_error',
                       'mean_squared_error', 'median_absolute_error',
-                      'max_error_scorer']
+                      'max_error']
 
 CLF_SCORERS = ['accuracy', 'balanced_accuracy',
                'f1', 'f1_weighted', 'f1_macro', 'f1_micro',

From 9f0f6de2802ae091820a11f4665df311c14e4c13 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 4 Oct 2018 13:39:44 +0530
Subject: [PATCH 08/23] Changes based on review comments

---
 sklearn/metrics/__init__.py   |  3 ++-
 sklearn/metrics/regression.py | 25 +++++++++++++++++--------
 2 files changed, 19 insertions(+), 9 deletions(-)

diff --git a/sklearn/metrics/__init__.py b/sklearn/metrics/__init__.py
index 5f0c5cd293115..6aa885a9d5315 100644
--- a/sklearn/metrics/__init__.py
+++ b/sklearn/metrics/__init__.py
@@ -55,12 +55,13 @@
 from .pairwise import pairwise_distances_chunked
 
 from .regression import explained_variance_score
+from .regression import max_error
 from .regression import mean_absolute_error
 from .regression import mean_squared_error
 from .regression import mean_squared_log_error
 from .regression import median_absolute_error
 from .regression import r2_score
-from .regression import max_error
+
 
 from .scorer import check_scoring
 from .scorer import make_scorer
diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
index bce878dc306fc..9d66a71641bad 100644
--- a/sklearn/metrics/regression.py
+++ b/sklearn/metrics/regression.py
@@ -31,13 +31,13 @@
 
 
 __ALL__ = [
+    "max_error",
     "mean_absolute_error",
     "mean_squared_error",
     "mean_squared_log_error",
     "median_absolute_error",
     "r2_score",
-    "explained_variance_score",
-    "max_error"
+    "explained_variance_score"
 ]
 
 
@@ -576,7 +576,7 @@ def r2_score(y_true, y_pred, sample_weight=None,
     return np.average(output_scores, weights=avg_weights)
 
 
-def max_error(y_true, y_pred):
+def max_error(y_true, y_pred, sample_weight=None):
     """
     The Max-Error metric is the worst case error
     between the predicted value and the true value.
@@ -589,6 +589,9 @@ def max_error(y_true, y_pred):
     y_pred : array-like of shape = (n_samples)
         Estimated target values.
 
+    sample_weight : array-like of shape = (n_samples), optional
+        Sample weights.
+
     Returns
     -------
     max_error : float
@@ -597,14 +600,20 @@ def max_error(y_true, y_pred):
     Examples
     --------
     >>> from sklearn.metrics import max_error
-    >>> y_true = [3.1, 2.4, 7.6, 1.9]
-    >>> y_pred = [4.1, 2.3, 7.4, 1.7]
+    >>> y_true = [3, 2, 7, 1]
+    >>> y_pred = [4, 2, 7, 1]
     >>> max_error(y_true, y_pred)
     1.0
     """
     y_type, y_true, y_pred, _ = _check_reg_targets(y_true, y_pred,
-                                                   'uniform_average')
+                                                   None)
+    check_consistent_length(y_true, y_pred, sample_weight)
     if y_type == 'continuous-multioutput':
         raise ValueError("Multioutput not supported in max_error")
-    max_error = np.around(np.max(np.abs(y_true - y_pred)), decimals=3)
-    return max_error
+
+    if sample_weight is not None:
+        sample_weight = column_or_1d(sample_weight)
+        weight = sample_weight[:, np.newaxis]
+    else:
+        weight = 1.
+    return np.max(np.abs(weight * (y_true - y_pred)))

From 495d6f0ccd2b3184224007b45b68ef274f01987f Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 4 Oct 2018 15:01:33 +0530
Subject: [PATCH 09/23] Sample weight initialization needs to be tweaked to
 make the test pass

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

diff --git a/sklearn/metrics/tests/test_score_objects.py b/sklearn/metrics/tests/test_score_objects.py
index 633caf9a9b339..34a3546c994ca 100644
--- a/sklearn/metrics/tests/test_score_objects.py
+++ b/sklearn/metrics/tests/test_score_objects.py
@@ -458,7 +458,7 @@ def test_scorer_sample_weight():
     X_train, X_test, y_train, y_test, y_ml_train, y_ml_test = split
 
     sample_weight = np.ones_like(y_test)
-    sample_weight[:10] = 0
+    sample_weight[:10] = 2
 
     # get sensible estimators for each metric
     estimator = _make_estimators(X_train, y_train, y_ml_train)

From 0ab351346d297fc939c06949e498b1426bc311ed Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 4 Oct 2018 15:27:52 +0530
Subject: [PATCH 10/23] Update sample weight only for the max_error scorer

---
 sklearn/metrics/tests/test_score_objects.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/sklearn/metrics/tests/test_score_objects.py b/sklearn/metrics/tests/test_score_objects.py
index 34a3546c994ca..23f4581fbd1ec 100644
--- a/sklearn/metrics/tests/test_score_objects.py
+++ b/sklearn/metrics/tests/test_score_objects.py
@@ -458,12 +458,14 @@ def test_scorer_sample_weight():
     X_train, X_test, y_train, y_test, y_ml_train, y_ml_test = split
 
     sample_weight = np.ones_like(y_test)
-    sample_weight[:10] = 2
+    sample_weight[:10] = 0
 
     # get sensible estimators for each metric
     estimator = _make_estimators(X_train, y_train, y_ml_train)
 
     for name, scorer in SCORERS.items():
+        if name == "max_error":
+            sample_weight[:10] = 2
         if name in MULTILABEL_ONLY_SCORERS:
             target = y_ml_test
         else:

From bb567610964c409d6a09d1acc5634cb704a4651a Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 4 Oct 2018 16:26:04 +0530
Subject: [PATCH 11/23] Change the sample weight slightly

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

diff --git a/sklearn/metrics/tests/test_score_objects.py b/sklearn/metrics/tests/test_score_objects.py
index 23f4581fbd1ec..7f36345645195 100644
--- a/sklearn/metrics/tests/test_score_objects.py
+++ b/sklearn/metrics/tests/test_score_objects.py
@@ -465,7 +465,7 @@ def test_scorer_sample_weight():
 
     for name, scorer in SCORERS.items():
         if name == "max_error":
-            sample_weight[:10] = 2
+            sample_weight[:10] = 1.01
         if name in MULTILABEL_ONLY_SCORERS:
             target = y_ml_test
         else:

From 7cfdb71cafd39639b139e3b4faa31553cacbea5c Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 4 Oct 2018 16:48:56 +0530
Subject: [PATCH 12/23] Remove support for sample weight

---
 sklearn/metrics/regression.py               | 15 ++++-----------
 sklearn/metrics/scorer.py                   |  3 ++-
 sklearn/metrics/tests/test_score_objects.py |  2 --
 3 files changed, 6 insertions(+), 14 deletions(-)

diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
index 9d66a71641bad..0037b9988cc26 100644
--- a/sklearn/metrics/regression.py
+++ b/sklearn/metrics/regression.py
@@ -576,10 +576,9 @@ def r2_score(y_true, y_pred, sample_weight=None,
     return np.average(output_scores, weights=avg_weights)
 
 
-def max_error(y_true, y_pred, sample_weight=None):
+def max_error(y_true, y_pred):
     """
-    The Max-Error metric is the worst case error
-    between the predicted value and the true value.
+    max_error metric calculates the maximum residual error.
 
     Parameters
     ----------
@@ -607,13 +606,7 @@ def max_error(y_true, y_pred, sample_weight=None):
     """
     y_type, y_true, y_pred, _ = _check_reg_targets(y_true, y_pred,
                                                    None)
-    check_consistent_length(y_true, y_pred, sample_weight)
+    check_consistent_length(y_true, y_pred)
     if y_type == 'continuous-multioutput':
         raise ValueError("Multioutput not supported in max_error")
-
-    if sample_weight is not None:
-        sample_weight = column_or_1d(sample_weight)
-        weight = sample_weight[:, np.newaxis]
-    else:
-        weight = 1.
-    return np.max(np.abs(weight * (y_true - y_pred)))
+    return np.max(np.abs(y_true - y_pred))
diff --git a/sklearn/metrics/scorer.py b/sklearn/metrics/scorer.py
index 84e5daa4f2307..f596d41637155 100644
--- a/sklearn/metrics/scorer.py
+++ b/sklearn/metrics/scorer.py
@@ -454,7 +454,8 @@ def make_scorer(score_func, greater_is_better=True, needs_proba=False,
 # Standard regression scores
 explained_variance_scorer = make_scorer(explained_variance_score)
 r2_scorer = make_scorer(r2_score)
-max_error_scorer = make_scorer(max_error)
+max_error_scorer = make_scorer(max_error,
+                               greater_is_better=False)
 neg_mean_squared_error_scorer = make_scorer(mean_squared_error,
                                             greater_is_better=False)
 neg_mean_squared_log_error_scorer = make_scorer(mean_squared_log_error,
diff --git a/sklearn/metrics/tests/test_score_objects.py b/sklearn/metrics/tests/test_score_objects.py
index 7f36345645195..633caf9a9b339 100644
--- a/sklearn/metrics/tests/test_score_objects.py
+++ b/sklearn/metrics/tests/test_score_objects.py
@@ -464,8 +464,6 @@ def test_scorer_sample_weight():
     estimator = _make_estimators(X_train, y_train, y_ml_train)
 
     for name, scorer in SCORERS.items():
-        if name == "max_error":
-            sample_weight[:10] = 1.01
         if name in MULTILABEL_ONLY_SCORERS:
             target = y_ml_test
         else:

From ae86ca4a55d6e91ea61ca80aaa1a4b41c0c45cd9 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 4 Oct 2018 16:59:41 +0530
Subject: [PATCH 13/23] Changes based on code review

---
 doc/modules/classes.rst              | 1 +
 sklearn/metrics/tests/test_common.py | 5 ++++-
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index 57ccfb5cff704..0084bb3f76b85 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -865,6 +865,7 @@ details.
    :template: function.rst
 
    metrics.explained_variance_score
+   metrics.max_error
    metrics.mean_absolute_error
    metrics.mean_squared_error
    metrics.mean_squared_log_error
diff --git a/sklearn/metrics/tests/test_common.py b/sklearn/metrics/tests/test_common.py
index 16e4f5d4c76da..21c5e97444db6 100644
--- a/sklearn/metrics/tests/test_common.py
+++ b/sklearn/metrics/tests/test_common.py
@@ -40,6 +40,7 @@
 from sklearn.metrics import label_ranking_average_precision_score
 from sklearn.metrics import label_ranking_loss
 from sklearn.metrics import log_loss
+from sklearn.metrics import max_error
 from sklearn.metrics import matthews_corrcoef
 from sklearn.metrics import mean_absolute_error
 from sklearn.metrics import mean_squared_error
@@ -89,6 +90,7 @@
 #
 
 REGRESSION_METRICS = {
+    "max_error": max_error,
     "mean_absolute_error": mean_absolute_error,
     "mean_squared_error": mean_squared_error,
     "median_absolute_error": median_absolute_error,
@@ -399,7 +401,7 @@ def precision_recall_curve_padded_thresholds(*args, **kwargs):
     "micro_precision_score", "micro_recall_score",
 
     "matthews_corrcoef_score", "mean_absolute_error", "mean_squared_error",
-    "median_absolute_error",
+    "median_absolute_error", "max_error",
 
     "cohen_kappa_score",
 }
@@ -429,6 +431,7 @@ def precision_recall_curve_padded_thresholds(*args, **kwargs):
 # No Sample weight support
 METRICS_WITHOUT_SAMPLE_WEIGHT = {
     "median_absolute_error",
+    "max_error"
 }
 
 

From d85f997b73c91e059726298099cf90e326eb27ef Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 4 Oct 2018 17:28:09 +0530
Subject: [PATCH 14/23] Fix the doctest

---
 sklearn/metrics/regression.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
index 0037b9988cc26..3718b8f2c95b9 100644
--- a/sklearn/metrics/regression.py
+++ b/sklearn/metrics/regression.py
@@ -588,9 +588,6 @@ def max_error(y_true, y_pred):
     y_pred : array-like of shape = (n_samples)
         Estimated target values.
 
-    sample_weight : array-like of shape = (n_samples), optional
-        Sample weights.
-
     Returns
     -------
     max_error : float
@@ -602,7 +599,7 @@ def max_error(y_true, y_pred):
     >>> y_true = [3, 2, 7, 1]
     >>> y_pred = [4, 2, 7, 1]
     >>> max_error(y_true, y_pred)
-    1.0
+    1
     """
     y_type, y_true, y_pred, _ = _check_reg_targets(y_true, y_pred,
                                                    None)

From 361675af298574c4a1e39473ca8ddd594f8385a9 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Sun, 7 Oct 2018 11:54:54 +0530
Subject: [PATCH 15/23] update what's new

---
 doc/whats_new/v0.21.rst | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/doc/whats_new/v0.21.rst b/doc/whats_new/v0.21.rst
index 27a756d9eefe5..f7234f59aa60a 100644
--- a/doc/whats_new/v0.21.rst
+++ b/doc/whats_new/v0.21.rst
@@ -52,6 +52,14 @@ Support for Python 3.4 and below has been officially dropped.
   graph, which would add explicitly zeros on the diagonal even when already
   present. :issue:`12105` by `Tom Dupre la Tour`_.
 
+
+:mod:`sklearn.metrics`
+......................
+
+- |Feature| A new regression metric: :class:`metrics.max_error`: a
+  metric that captures the max residual error, by :user:`Krishna Sangeeth <whiletruelearn>`.
+
+
 Multiple modules
 ................
 

From 5b82f0966a8a26a9b54680e8256d76e72c1e71ba Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Sun, 7 Oct 2018 11:57:27 +0530
Subject: [PATCH 16/23] Update the PR number also

---
 doc/whats_new/v0.21.rst | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/doc/whats_new/v0.21.rst b/doc/whats_new/v0.21.rst
index f7234f59aa60a..ed916a902f1e4 100644
--- a/doc/whats_new/v0.21.rst
+++ b/doc/whats_new/v0.21.rst
@@ -57,7 +57,8 @@ Support for Python 3.4 and below has been officially dropped.
 ......................
 
 - |Feature| A new regression metric: :class:`metrics.max_error`: a
-  metric that captures the max residual error, by :user:`Krishna Sangeeth <whiletruelearn>`.
+  metric that captures the max residual error.
+  :issue:`12232` by :user:`Krishna Sangeeth <whiletruelearn>`.
 
 
 Multiple modules

From e296cdda15c53944a4580df3e0eeca194455a6c3 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 8 Oct 2018 11:02:40 +0530
Subject: [PATCH 17/23] Update the user guide

---
 doc/modules/model_evaluation.rst | 30 ++++++++++++++++++++++++++++++
 1 file changed, 30 insertions(+)

diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
index 89bc3bb4a84e9..f20ccf303ebb1 100644
--- a/doc/modules/model_evaluation.rst
+++ b/doc/modules/model_evaluation.rst
@@ -84,6 +84,7 @@ Scoring                           Function
 
 **Regression**
 'explained_variance'              :func:`metrics.explained_variance_score`
+'max_error'                       :func:`metrics.max_error`
 'neg_mean_absolute_error'         :func:`metrics.mean_absolute_error`
 'neg_mean_squared_error'          :func:`metrics.mean_squared_error`
 'neg_mean_squared_log_error'      :func:`metrics.mean_squared_log_error`
@@ -1530,6 +1531,35 @@ function::
     ... # doctest: +ELLIPSIS
     0.990...
 
+
+
+Max error
+-------------------
+
+The :func:`max_error` function computes the  maximum `residual error <https://en.wikipedia.org/wiki/Errors_and_residuals`_,
+a metric that captures the worst case error between the predicted value and the true value.
+In a perfectly fitted single output regression model, `max_error` would be `0` and though this
+would be highly unlikely in the real world, this metric shows the extent of error that the
+model had when it was fitted.
+
+
+If :math:`\hat{y}_i` is the predicted value of the :math:`i`-th sample,
+and :math:`y_i` is the corresponding true value, then the max error is defined as
+
+.. math::
+
+  \text{Max Error}(y, \hat{y}) = max(| y_i - \hat{y}_i |)
+
+Here is a small example of usage of the :func:`max_error` function::
+
+  >>> from sklearn.metrics import max_error
+  >>> y_true = [3, 2, 7, 1]
+  >>> y_pred = [4, 2, 7, 1]
+  >>> max_error(y_true, y_pred)
+  1
+
+The :func:`max_error` does not support multioutput.
+
 .. _mean_absolute_error:
 
 Mean absolute error

From ff3550448b0d78b257759857319e40a422dda0db Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 8 Oct 2018 14:10:56 +0530
Subject: [PATCH 18/23] update the documentation based on review comments

---
 doc/modules/model_evaluation.rst | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
index f20ccf303ebb1..c19faefd6820b 100644
--- a/doc/modules/model_evaluation.rst
+++ b/doc/modules/model_evaluation.rst
@@ -1538,8 +1538,8 @@ Max error
 
 The :func:`max_error` function computes the  maximum `residual error <https://en.wikipedia.org/wiki/Errors_and_residuals`_,
 a metric that captures the worst case error between the predicted value and the true value.
-In a perfectly fitted single output regression model, `max_error` would be `0` and though this
-would be highly unlikely in the real world, this metric shows the extent of error that the
+In a perfectly fitted single output regression model, `max_error` would be `0` on the training set
+and though this would be highly unlikely in the real world, this metric shows the extent of error that the
 model had when it was fitted.
 
 
@@ -1554,9 +1554,9 @@ Here is a small example of usage of the :func:`max_error` function::
 
   >>> from sklearn.metrics import max_error
   >>> y_true = [3, 2, 7, 1]
-  >>> y_pred = [4, 2, 7, 1]
+  >>> y_pred = [9, 2, 7, 1]
   >>> max_error(y_true, y_pred)
-  1
+  6
 
 The :func:`max_error` does not support multioutput.
 

From cb50f2304d85b14a66f742b234f2446ab0a3d8c5 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Mon, 8 Oct 2018 20:00:08 +0530
Subject: [PATCH 19/23] Add reference and style fix for doc to have 80 char
 limit

---
 doc/modules/model_evaluation.rst | 17 ++++++++++-------
 sklearn/metrics/regression.py    |  2 ++
 2 files changed, 12 insertions(+), 7 deletions(-)

diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
index c19faefd6820b..ef1d5096cf32a 100644
--- a/doc/modules/model_evaluation.rst
+++ b/doc/modules/model_evaluation.rst
@@ -1531,20 +1531,23 @@ function::
     ... # doctest: +ELLIPSIS
     0.990...
 
-
+.. _max_error:
 
 Max error
 -------------------
 
-The :func:`max_error` function computes the  maximum `residual error <https://en.wikipedia.org/wiki/Errors_and_residuals`_,
-a metric that captures the worst case error between the predicted value and the true value.
-In a perfectly fitted single output regression model, `max_error` would be `0` on the training set
-and though this would be highly unlikely in the real world, this metric shows the extent of error that the
-model had when it was fitted.
+The :func:`max_error` function computes the  maximum `residual error
+<https://en.wikipedia.org/wiki/Errors_and_residuals>`_ ,a metric
+that captures the worst case error between the predicted value and
+the true value. In a perfectly fitted single output regression
+model, `max_error` would be `0` on the training set and though this
+would be highly unlikely in the real world, this metric shows the
+extent of error that the model had when it was fitted.
 
 
 If :math:`\hat{y}_i` is the predicted value of the :math:`i`-th sample,
-and :math:`y_i` is the corresponding true value, then the max error is defined as
+and :math:`y_i` is the corresponding true value, then the max error is
+defined as
 
 .. math::
 
diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
index 3718b8f2c95b9..fbee56306f131 100644
--- a/sklearn/metrics/regression.py
+++ b/sklearn/metrics/regression.py
@@ -580,6 +580,8 @@ def max_error(y_true, y_pred):
     """
     max_error metric calculates the maximum residual error.
 
+    Read more in the :ref:`User Guide <max_error>`.
+
     Parameters
     ----------
     y_true : array-like of shape = (n_samples)

From f156d5974e30b48ea573c1ac2e76b969eaa042b9 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 11 Oct 2018 00:11:46 +0530
Subject: [PATCH 20/23] Update review comments

---
 doc/modules/model_evaluation.rst | 4 ++--
 sklearn/metrics/regression.py    | 3 +--
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
index ef1d5096cf32a..d56356c2f1949 100644
--- a/doc/modules/model_evaluation.rst
+++ b/doc/modules/model_evaluation.rst
@@ -1537,10 +1537,10 @@ Max error
 -------------------
 
 The :func:`max_error` function computes the  maximum `residual error
-<https://en.wikipedia.org/wiki/Errors_and_residuals>`_ ,a metric
+<https://en.wikipedia.org/wiki/Errors_and_residuals>`_ , a metric
 that captures the worst case error between the predicted value and
 the true value. In a perfectly fitted single output regression
-model, `max_error` would be `0` on the training set and though this
+model, ``max_error`` would be ``0`` on the training set and though this
 would be highly unlikely in the real world, this metric shows the
 extent of error that the model had when it was fitted.
 
diff --git a/sklearn/metrics/regression.py b/sklearn/metrics/regression.py
index fbee56306f131..f4854ff244bc4 100644
--- a/sklearn/metrics/regression.py
+++ b/sklearn/metrics/regression.py
@@ -603,8 +603,7 @@ def max_error(y_true, y_pred):
     >>> max_error(y_true, y_pred)
     1
     """
-    y_type, y_true, y_pred, _ = _check_reg_targets(y_true, y_pred,
-                                                   None)
+    y_type, y_true, y_pred, _ = _check_reg_targets(y_true, y_pred, None)
     check_consistent_length(y_true, y_pred)
     if y_type == 'continuous-multioutput':
         raise ValueError("Multioutput not supported in max_error")

From 3e0dfcf26dbc2f4a9883798778acc125c495c3c4 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 11 Oct 2018 11:00:13 +0530
Subject: [PATCH 21/23] Doc updates

---
 doc/modules/model_evaluation.rst | 2 +-
 doc/whats_new/v0.21.rst          | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
index d56356c2f1949..9c4e7efdacf6f 100644
--- a/doc/modules/model_evaluation.rst
+++ b/doc/modules/model_evaluation.rst
@@ -1536,7 +1536,7 @@ function::
 Max error
 -------------------
 
-The :func:`max_error` function computes the  maximum `residual error
+The :func:`max_error` function computes the maximum `residual error
 <https://en.wikipedia.org/wiki/Errors_and_residuals>`_ , a metric
 that captures the worst case error between the predicted value and
 the true value. In a perfectly fitted single output regression
diff --git a/doc/whats_new/v0.21.rst b/doc/whats_new/v0.21.rst
index ed916a902f1e4..97d66a2161098 100644
--- a/doc/whats_new/v0.21.rst
+++ b/doc/whats_new/v0.21.rst
@@ -57,7 +57,8 @@ Support for Python 3.4 and below has been officially dropped.
 ......................
 
 - |Feature| A new regression metric: :class:`metrics.max_error`: a
-  metric that captures the max residual error.
+  metric that captures the maximum residual error and a corresponding
+  ``'max_error'`` scorer for single output regression .
   :issue:`12232` by :user:`Krishna Sangeeth <whiletruelearn>`.
 
 

From a088a76129ad5980867a7ad7db1976441c2f9f46 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 11 Oct 2018 11:13:07 +0530
Subject: [PATCH 22/23] Better structuring of sentence

---
 doc/whats_new/v0.21.rst | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/doc/whats_new/v0.21.rst b/doc/whats_new/v0.21.rst
index 97d66a2161098..e969a0420dfb2 100644
--- a/doc/whats_new/v0.21.rst
+++ b/doc/whats_new/v0.21.rst
@@ -56,9 +56,8 @@ Support for Python 3.4 and below has been officially dropped.
 :mod:`sklearn.metrics`
 ......................
 
-- |Feature| A new regression metric: :class:`metrics.max_error`: a
-  metric that captures the maximum residual error and a corresponding
-  ``'max_error'`` scorer for single output regression .
+- |Feature| Added the :func:`metrics.max_error` and a corresponding
+  ``'max_error'`` scorer for single output regression.
   :issue:`12232` by :user:`Krishna Sangeeth <whiletruelearn>`.
 
 

From 90d69dbf944194c8aa0cb8942ca65fb1832b79f3 Mon Sep 17 00:00:00 2001
From: Krishna Sangeeth <kskrishnasangeeth@gmail.com>
Date: Thu, 11 Oct 2018 11:14:24 +0530
Subject: [PATCH 23/23] Missed to add the word metric

---
 doc/whats_new/v0.21.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/whats_new/v0.21.rst b/doc/whats_new/v0.21.rst
index e969a0420dfb2..d560f980beb91 100644
--- a/doc/whats_new/v0.21.rst
+++ b/doc/whats_new/v0.21.rst
@@ -56,7 +56,7 @@ Support for Python 3.4 and below has been officially dropped.
 :mod:`sklearn.metrics`
 ......................
 
-- |Feature| Added the :func:`metrics.max_error` and a corresponding
+- |Feature| Added the :func:`metrics.max_error` metric and a corresponding
   ``'max_error'`` scorer for single output regression.
   :issue:`12232` by :user:`Krishna Sangeeth <whiletruelearn>`.