dev/visualizations.html



<!DOCTYPE html>
<!-- data-theme below is forced to be "light" but should be changed if we use pydata-theme-sphinx in the future -->
<!--[if IE 8]><html class="no-js lt-ie9" lang="en" data-content_root="./" data-theme="light"> <![endif]-->
<!--[if gt IE 8]><!--> <html class="no-js" lang="en" data-content_root="./" data-theme="light"> <!--<![endif]-->
<head>
  <meta charset="utf-8">
  <meta name="viewport" content="width=device-width, initial-scale=1" />
<meta property="og:title" content="5. Visualizations" />
<meta property="og:type" content="website" />
<meta property="og:url" content="https://scikit-learn/stable/visualizations.html" />
<meta property="og:site_name" content="scikit-learn" />
<meta property="og:description" content="Scikit-learn defines a simple API for creating visualizations for machine learning. The key feature of this API is to allow for quick plotting and visual adjustments without recalculation. We provi..." />
<meta property="og:image" content="https://scikit-learn/stable/_images/visualizations-1.png" />
<meta property="og:image:alt" content="scikit-learn" />
<meta name="description" content="Scikit-learn defines a simple API for creating visualizations for machine learning. The key feature of this API is to allow for quick plotting and visual adjustments without recalculation. We provi..." />

  <meta name="viewport" content="width=device-width, initial-scale=1.0">

  
  <title>5. Visualizations &mdash; scikit-learn 1.5.dev0 documentation</title>
  
  <link rel="canonical" href="http://scikit-learn.org/stable/visualizations.html" />

  
  <link rel="shortcut icon" href="_static/favicon.ico"/>
  

  <link rel="stylesheet" href="_static/css/vendor/bootstrap.min.css" type="text/css" />
  <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
  <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
  <link rel="stylesheet" href="_static/copybutton.css" type="text/css" />
  <link rel="stylesheet" href="_static/plot_directive.css" type="text/css" />
  <link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Vibur" type="text/css" />
  <link rel="stylesheet" href="_static/jupyterlite_sphinx.css" type="text/css" />
  <link rel="stylesheet" href="_static/sg_gallery.css" type="text/css" />
  <link rel="stylesheet" href="_static/sg_gallery-binder.css" type="text/css" />
  <link rel="stylesheet" href="_static/sg_gallery-dataframe.css" type="text/css" />
  <link rel="stylesheet" href="_static/sg_gallery-rendered-html.css" type="text/css" />
  <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
<script id="documentation_options" data-url_root="./" src="_static/documentation_options.js"></script>
<script src="_static/js/vendor/jquery-3.6.3.slim.min.js"></script>
<script src="_static/js/details-permalink.js"></script> 
</head>
<body>


<nav id="navbar" class="sk-docs-navbar navbar navbar-expand-md navbar-light bg-light py-0">
  <div class="container-fluid sk-docs-container px-0">
      <a class="navbar-brand py-0" href="index.html">
        <img
          class="sk-brand-img"
          src="_static/scikit-learn-logo-small.png"
          alt="logo"/>
      </a>
    <button
      id="sk-navbar-toggler"
      class="navbar-toggler"
      type="button"
      data-toggle="collapse"
      data-target="#navbarSupportedContent"
      aria-controls="navbarSupportedContent"
      aria-expanded="false"
      aria-label="Toggle navigation"
    >
      <span class="navbar-toggler-icon"></span>
    </button>

    <div class="sk-navbar-collapse collapse navbar-collapse" id="navbarSupportedContent">
      <ul class="navbar-nav mr-auto">
        <li class="nav-item">
          <a class="sk-nav-link nav-link" href="install.html">Install</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link" href="user_guide.html">User Guide</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link" href="modules/classes.html">API</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link" href="auto_examples/index.html">Examples</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link" target="_blank" rel="noopener noreferrer" href="https://blog.scikit-learn.org/">Community</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="getting_started.html" >Getting Started</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="tutorial/index.html" >Tutorial</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="whats_new/v1.5.html" >What's new</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="glossary.html" >Glossary</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="developers/index.html" >Development</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="faq.html" >FAQ</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="support.html" >Support</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="related_projects.html" >Related packages</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="roadmap.html" >Roadmap</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="governance.html" >Governance</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="about.html" >About us</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="https://github.com/scikit-learn/scikit-learn" >GitHub</a>
        </li>
        <li class="nav-item">
          <a class="sk-nav-link nav-link nav-more-item-mobile-items" href="https://scikit-learn.org/dev/versions.html" >Other Versions and Download</a>
        </li>
        <li class="nav-item dropdown nav-more-item-dropdown">
          <a class="sk-nav-link nav-link dropdown-toggle" href="#" id="navbarDropdown" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false">More</a>
          <div class="dropdown-menu" aria-labelledby="navbarDropdown">
              <a class="sk-nav-dropdown-item dropdown-item" href="getting_started.html" >Getting Started</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="tutorial/index.html" >Tutorial</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="whats_new/v1.5.html" >What's new</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="glossary.html" >Glossary</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="developers/index.html" >Development</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="faq.html" >FAQ</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="support.html" >Support</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="related_projects.html" >Related packages</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="roadmap.html" >Roadmap</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="governance.html" >Governance</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="about.html" >About us</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="https://github.com/scikit-learn/scikit-learn" >GitHub</a>
              <a class="sk-nav-dropdown-item dropdown-item" href="https://scikit-learn.org/dev/versions.html" >Other Versions and Download</a>
          </div>
        </li>
      </ul>
      <div id="searchbox" role="search">
          <div class="searchformwrapper">
          <form class="search" action="search.html" method="get">
            <input class="sk-search-text-input" type="text" name="q" aria-labelledby="searchlabel" />
            <input class="sk-search-text-btn" type="submit" value="Go" />
          </form>
          </div>
      </div>
    </div>
  </div>
</nav>
<div class="d-flex" id="sk-doc-wrapper">
    <input type="checkbox" name="sk-toggle-checkbox" id="sk-toggle-checkbox">
    <label id="sk-sidemenu-toggle" class="sk-btn-toggle-toc btn sk-btn-primary" for="sk-toggle-checkbox">Toggle Menu</label>
    <div id="sk-sidebar-wrapper" class="border-right">
      <div class="sk-sidebar-toc-wrapper">
        <div class="btn-group w-100 mb-2" role="group" aria-label="rellinks">
            <a href="modules/permutation_importance.html" role="button" class="btn sk-btn-rellink py-1" sk-rellink-tooltip="4.2. Permutation feature importance">Prev</a><a href="user_guide.html" role="button" class="btn sk-btn-rellink py-1" sk-rellink-tooltip="User Guide">Up</a>
            <a href="data_transforms.html" role="button" class="btn sk-btn-rellink py-1" sk-rellink-tooltip="6. Dataset transformations">Next</a>
        </div>
        <div class="alert alert-danger p-1 mb-2" role="alert">
          <p class="text-center mb-0">
          <strong>scikit-learn 1.5.dev0</strong><br/>
          <a href="http://scikit-learn.org/dev/versions.html">Other versions</a>
          </p>
        </div>
        <div class="alert alert-warning p-1 mb-2" role="alert">
          <p class="text-center mb-0">
            Please <a class="font-weight-bold" href="about.html#citing-scikit-learn"><string>cite us</string></a> if you use the software.
          </p>
        </div>
            <div class="sk-sidebar-toc">
            
              <ul>
              
              
              <li>
                <a href="user_guide.html" class="sk-toc-active">User Guide</a>
              </li>
              <ul>
              
                <li>
                  <a href="supervised_learning.html" class="">1. Supervised learning</a>
                  
                </li>
              
                <li>
                  <a href="unsupervised_learning.html" class="">2. Unsupervised learning</a>
                  
                </li>
              
                <li>
                  <a href="model_selection.html" class="">3. Model selection and evaluation</a>
                  
                </li>
              
                <li>
                  <a href="inspection.html" class="">4. Inspection</a>
                  
                </li>
              
                <li>
                  <a href="" class="sk-toc-active">5. Visualizations</a>
                  
                </li>
              
                <li>
                  <a href="data_transforms.html" class="">6. Dataset transformations</a>
                  
                </li>
              
                <li>
                  <a href="datasets.html" class="">7. Dataset loading utilities</a>
                  
                </li>
              
                <li>
                  <a href="computing.html" class="">8. Computing with scikit-learn</a>
                  
                </li>
              
                <li>
                  <a href="model_persistence.html" class="">9. Model persistence</a>
                  
                </li>
              
                <li>
                  <a href="common_pitfalls.html" class="">10. Common pitfalls and recommended practices</a>
                  
                </li>
              
                <li>
                  <a href="dispatching.html" class="">11. Dispatching</a>
                  
                </li>
              
              </ul>
              
              
              </ul>
            </div>
      </div>
    </div>
    <div id="sk-page-content-wrapper">
      <div class="sk-page-content container-fluid body px-md-3" role="main">
        
  <style type="text/css">
  div.body div.toctree-wrapper ul {
      padding-left: 0;
  }

  div.body li.toctree-l1 {
      padding: 0 0 0.5em 0;
      list-style-type: none;
      font-size: 150%;
      font-weight: bold;
  }

  div.body li.toctree-l2 {
      font-size: 70%;
      list-style-type: square;
      font-weight: normal;
      margin-left: 40px;
  }

  div.body li.toctree-l3 {
      font-size: 85%;
      list-style-type: circle;
      font-weight: normal;
      margin-left: 40px;
  }

  div.body li.toctree-l4 {
      margin-left: 40px;
  }

</style><section id="visualizations">
<span id="id1"></span><h1><span class="section-number">5. </span>Visualizations<a class="headerlink" href="#visualizations" title="Link to this heading">¶</a></h1>
<p>Scikit-learn defines a simple API for creating visualizations for machine
learning. The key feature of this API is to allow for quick plotting and
visual adjustments without recalculation. We provide <code class="docutils literal notranslate"><span class="pre">Display</span></code> classes that
expose two methods for creating plots: <code class="docutils literal notranslate"><span class="pre">from_estimator</span></code> and
<code class="docutils literal notranslate"><span class="pre">from_predictions</span></code>. The <code class="docutils literal notranslate"><span class="pre">from_estimator</span></code> method will take a fitted estimator
and some data (<code class="docutils literal notranslate"><span class="pre">X</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code>) and create a <code class="docutils literal notranslate"><span class="pre">Display</span></code> object. Sometimes, we would
like to only compute the predictions once and one should use <code class="docutils literal notranslate"><span class="pre">from_predictions</span></code>
instead. In the following example, we plot a ROC curve for a fitted support
vector machine:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="kn">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">sklearn.svm</span> <span class="kn">import</span> <span class="n">SVC</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <span class="n">RocCurveDisplay</span>
<span class="kn">from</span> <span class="nn">sklearn.datasets</span> <span class="kn">import</span> <span class="n">load_wine</span>

<span class="n">X</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">load_wine</span><span class="p">(</span><span class="n">return_X_y</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">y</span> <span class="o">==</span> <span class="mi">2</span>  <span class="c1"># make binary</span>
<span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="n">svc</span> <span class="o">=</span> <span class="n">SVC</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="n">svc</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>

<span class="n">svc_disp</span> <span class="o">=</span> <span class="n">RocCurveDisplay</span><span class="o">.</span><span class="n">from_estimator</span><span class="p">(</span><span class="n">svc</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span><span class="p">)</span>
</pre></div>
</div>
<figure class="align-center">
<img alt="_images/visualizations-1.png" class="plot-directive" src="_images/visualizations-1.png" />
</figure>
<p>The returned <code class="docutils literal notranslate"><span class="pre">svc_disp</span></code> object allows us to continue using the already computed
ROC curve for SVC in future plots. In this case, the <code class="docutils literal notranslate"><span class="pre">svc_disp</span></code> is a
<a class="reference internal" href="modules/generated/sklearn.metrics.RocCurveDisplay.html#sklearn.metrics.RocCurveDisplay" title="sklearn.metrics.RocCurveDisplay"><code class="xref py py-class docutils literal notranslate"><span class="pre">RocCurveDisplay</span></code></a> that stores the computed values as
attributes called <code class="docutils literal notranslate"><span class="pre">roc_auc</span></code>, <code class="docutils literal notranslate"><span class="pre">fpr</span></code>, and <code class="docutils literal notranslate"><span class="pre">tpr</span></code>. Be aware that we could get
the predictions from the support vector machine and then use <code class="docutils literal notranslate"><span class="pre">from_predictions</span></code>
instead of <code class="docutils literal notranslate"><span class="pre">from_estimator</span></code>. Next, we train a random forest classifier and plot
the previously computed roc curve again by using the <code class="docutils literal notranslate"><span class="pre">plot</span></code> method of the
<code class="docutils literal notranslate"><span class="pre">Display</span></code> object.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="kn">import</span> <span class="n">RandomForestClassifier</span>

<span class="n">rfc</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="n">rfc</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>

<span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">gca</span><span class="p">()</span>
<span class="n">rfc_disp</span> <span class="o">=</span> <span class="n">RocCurveDisplay</span><span class="o">.</span><span class="n">from_estimator</span><span class="p">(</span><span class="n">rfc</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.8</span><span class="p">)</span>
<span class="n">svc_disp</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.8</span><span class="p">)</span>
</pre></div>
</div>
<figure class="align-center">
<img alt="_images/visualizations-2.png" class="plot-directive" src="_images/visualizations-2.png" />
</figure>
<p>Notice that we pass <code class="docutils literal notranslate"><span class="pre">alpha=0.8</span></code> to the plot functions to adjust the alpha
values of the curves.</p>
<aside class="topic">
<p class="topic-title">Examples:</p>
<ul class="simple">
<li><p><a class="reference internal" href="auto_examples/miscellaneous/plot_roc_curve_visualization_api.html#sphx-glr-auto-examples-miscellaneous-plot-roc-curve-visualization-api-py"><span class="std std-ref">ROC Curve with Visualization API</span></a></p></li>
<li><p><a class="reference internal" href="auto_examples/miscellaneous/plot_partial_dependence_visualization_api.html#sphx-glr-auto-examples-miscellaneous-plot-partial-dependence-visualization-api-py"><span class="std std-ref">Advanced Plotting With Partial Dependence</span></a></p></li>
<li><p><a class="reference internal" href="auto_examples/miscellaneous/plot_display_object_visualization.html#sphx-glr-auto-examples-miscellaneous-plot-display-object-visualization-py"><span class="std std-ref">Visualizations with Display Objects</span></a></p></li>
<li><p><a class="reference internal" href="auto_examples/calibration/plot_compare_calibration.html#sphx-glr-auto-examples-calibration-plot-compare-calibration-py"><span class="std std-ref">Comparison of Calibration of Classifiers</span></a></p></li>
</ul>
</aside>
<section id="available-plotting-utilities">
<h2><span class="section-number">5.1. </span>Available Plotting Utilities<a class="headerlink" href="#available-plotting-utilities" title="Link to this heading">¶</a></h2>
<section id="display-objects">
<h3><span class="section-number">5.1.1. </span>Display Objects<a class="headerlink" href="#display-objects" title="Link to this heading">¶</a></h3>
<table class="autosummary longtable docutils align-default">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="modules/generated/sklearn.calibration.CalibrationDisplay.html#sklearn.calibration.CalibrationDisplay" title="sklearn.calibration.CalibrationDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">calibration.CalibrationDisplay</span></code></a>(prob_true, ...)</p></td>
<td><p>Calibration curve (also known as reliability diagram) visualization.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="modules/generated/sklearn.inspection.PartialDependenceDisplay.html#sklearn.inspection.PartialDependenceDisplay" title="sklearn.inspection.PartialDependenceDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">inspection.PartialDependenceDisplay</span></code></a>(...[, ...])</p></td>
<td><p>Partial Dependence Plot (PDP).</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="modules/generated/sklearn.inspection.DecisionBoundaryDisplay.html#sklearn.inspection.DecisionBoundaryDisplay" title="sklearn.inspection.DecisionBoundaryDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">inspection.DecisionBoundaryDisplay</span></code></a>(*, xx0, ...)</p></td>
<td><p>Decisions boundary visualization.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="modules/generated/sklearn.metrics.ConfusionMatrixDisplay.html#sklearn.metrics.ConfusionMatrixDisplay" title="sklearn.metrics.ConfusionMatrixDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">metrics.ConfusionMatrixDisplay</span></code></a>(...[, ...])</p></td>
<td><p>Confusion Matrix visualization.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="modules/generated/sklearn.metrics.DetCurveDisplay.html#sklearn.metrics.DetCurveDisplay" title="sklearn.metrics.DetCurveDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">metrics.DetCurveDisplay</span></code></a>(*, fpr, fnr[, ...])</p></td>
<td><p>DET curve visualization.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="modules/generated/sklearn.metrics.PrecisionRecallDisplay.html#sklearn.metrics.PrecisionRecallDisplay" title="sklearn.metrics.PrecisionRecallDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">metrics.PrecisionRecallDisplay</span></code></a>(precision, ...)</p></td>
<td><p>Precision Recall visualization.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="modules/generated/sklearn.metrics.PredictionErrorDisplay.html#sklearn.metrics.PredictionErrorDisplay" title="sklearn.metrics.PredictionErrorDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">metrics.PredictionErrorDisplay</span></code></a>(*, y_true, y_pred)</p></td>
<td><p>Visualization of the prediction error of a regression model.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="modules/generated/sklearn.metrics.RocCurveDisplay.html#sklearn.metrics.RocCurveDisplay" title="sklearn.metrics.RocCurveDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">metrics.RocCurveDisplay</span></code></a>(*, fpr, tpr[, ...])</p></td>
<td><p>ROC Curve visualization.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="modules/generated/sklearn.model_selection.LearningCurveDisplay.html#sklearn.model_selection.LearningCurveDisplay" title="sklearn.model_selection.LearningCurveDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">model_selection.LearningCurveDisplay</span></code></a>(*, ...)</p></td>
<td><p>Learning Curve visualization.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="modules/generated/sklearn.model_selection.ValidationCurveDisplay.html#sklearn.model_selection.ValidationCurveDisplay" title="sklearn.model_selection.ValidationCurveDisplay"><code class="xref py py-obj docutils literal notranslate"><span class="pre">model_selection.ValidationCurveDisplay</span></code></a>(*, ...)</p></td>
<td><p>Validation Curve visualization.</p></td>
</tr>
</tbody>
</table>
</section>
</section>
</section>


      </div>
    <div class="container">
      <footer class="sk-content-footer">
            &copy; 2007 - 2024, scikit-learn developers (BSD License).
          <a href="_sources/visualizations.rst.txt" rel="nofollow">Show this page source</a>
      </footer>
    </div>
  </div>
</div>
<script src="_static/js/vendor/bootstrap.min.js"></script>

<script>
    window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)};ga.l=+new Date;
    ga('create', 'UA-22606712-2', 'auto');
    ga('set', 'anonymizeIp', true);
    ga('send', 'pageview');
</script>
<script async src='https://www.google-analytics.com/analytics.js'></script>


<script defer data-domain="scikit-learn.org" src="https://views.scientific-python.org/js/script.js">
</script>


<script src="_static/clipboard.min.js"></script>
<script src="_static/copybutton.js"></script>

<script>
$(document).ready(function() {
    /* Add a [>>>] button on the top-right corner of code samples to hide
     * the >>> and ... prompts and the output and thus make the code
     * copyable. */
    var div = $('.highlight-python .highlight,' +
                '.highlight-python3 .highlight,' +
                '.highlight-pycon .highlight,' +
		'.highlight-default .highlight')
    var pre = div.find('pre');

    // get the styles from the current theme
    pre.parent().parent().css('position', 'relative');

    // create and add the button to all the code blocks that contain >>>
    div.each(function(index) {
        var jthis = $(this);
        // tracebacks (.gt) contain bare text elements that need to be
        // wrapped in a span to work with .nextUntil() (see later)
        jthis.find('pre:has(.gt)').contents().filter(function() {
            return ((this.nodeType == 3) && (this.data.trim().length > 0));
        }).wrap('<span>');
    });

	/*** Add permalink buttons next to glossary terms ***/
	$('dl.glossary > dt[id]').append(function() {
		return ('<a class="headerlink" href="#' +
			    this.getAttribute('id') +
			    '" title="Permalink to this term">¶</a>');
	});
});

</script>
    
<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-chtml.js"></script>
    
    <script src="https://scikit-learn.org/versionwarning.js"></script>
</body>
</html>