From a9c6c69960b05282fccd2560732b268f5df4c356 Mon Sep 17 00:00:00 2001
From: Daniel Thoren <s144222@student.dtu.dk>
Date: Thu, 14 May 2020 16:58:19 +0200
Subject: [PATCH] Fix incorrect source code link

---
 0.23/modules/generated/sklearn.metrics.f1_score.html | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/0.23/modules/generated/sklearn.metrics.f1_score.html b/0.23/modules/generated/sklearn.metrics.f1_score.html
index c9b7e9a434eb1..56523dd576376 100644
--- a/0.23/modules/generated/sklearn.metrics.f1_score.html
+++ b/0.23/modules/generated/sklearn.metrics.f1_score.html
@@ -169,7 +169,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.metrics" title="sklearn.metrics"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.metrics</span></code></a>.f1_score<a class="headerlink" href="#sklearn-metrics-f1-score" title="Permalink to this headline">¶</a></h1>
 <dl class="function">
 <dt id="sklearn.metrics.f1_score">
-<code class="sig-prename descclassname">sklearn.metrics.</code><code class="sig-name descname">f1_score</code><span class="sig-paren">(</span><em class="sig-param">y_true</em>, <em class="sig-param">y_pred</em>, <em class="sig-param">*</em>, <em class="sig-param">labels=None</em>, <em class="sig-param">pos_label=1</em>, <em class="sig-param">average='binary'</em>, <em class="sig-param">sample_weight=None</em>, <em class="sig-param">zero_division='warn'</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/483cd3eaa/sklearn/utils/validation.py#L925"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.metrics.f1_score" title="Permalink to this definition">¶</a></dt>
+<code class="sig-prename descclassname">sklearn.metrics.</code><code class="sig-name descname">f1_score</code><span class="sig-paren">(</span><em class="sig-param">y_true</em>, <em class="sig-param">y_pred</em>, <em class="sig-param">*</em>, <em class="sig-param">labels=None</em>, <em class="sig-param">pos_label=1</em>, <em class="sig-param">average='binary'</em>, <em class="sig-param">sample_weight=None</em>, <em class="sig-param">zero_division='warn'</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/483cd3eaa/sklearn/metrics/_classification.py#L926"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.metrics.f1_score" title="Permalink to this definition">¶</a></dt>
 <dd><p>Compute the F1 score, also known as balanced F-score or F-measure</p>
 <p>The F1 score can be interpreted as a weighted average of the precision and
 recall, where an F1 score reaches its best value at 1 and worst score at 0.
@@ -454,4 +454,4 @@ <h2>Examples using <code class="docutils literal notranslate"><span class="pre">
     
     <script src="https://scikit-learn.org/versionwarning.js"></script>
 </body>
-</html>
\ No newline at end of file
+</html>