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probabl-ai · Nov 8, 2024 · 07c442d · 07c442d
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diff --git a/docs/latest/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/docs/latest/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
diff --git a/docs/latest/_downloads/6a98626692e1880e5e2663974edc45be/plot_02_overview_skore_ui.zip b/docs/latest/_downloads/6a98626692e1880e5e2663974edc45be/plot_02_overview_skore_ui.zip
diff --git a/docs/latest/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/docs/latest/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip
diff --git a/docs/latest/_downloads/97b4b84f5410e1134b3cbe5e4682d2a1/plot_01_getting_started.zip b/docs/latest/_downloads/97b4b84f5410e1134b3cbe5e4682d2a1/plot_01_getting_started.zip
diff --git a/docs/latest/_downloads/9825adffd8a0e006b517b57261e52107/plot_03_cross_validate.ipynb b/docs/latest/_downloads/9825adffd8a0e006b517b57261e52107/plot_03_cross_validate.ipynb
@@ -158,6 +158,31 @@
         "### Regression task\n\n"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "For now, all cross-validation runs store their results in the same place, which might\nlead to comparing two different models that are actually not comparable (e.g.\ncomparing a regression with a classification).\nTo remedy this, we clear the cross-validation information stored in skore before\nrunning another unrelated cross-validation:\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "my_project_gs.delete_item(\"cross_validation\")\nmy_project_gs.delete_item(\"cross_validation_aggregated\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div class=\"alert alert-info\"><h4>Note</h4><p>Soon, the storage of several unrelated cross-validation runs will be managed\n  automatically.</p></div>\n\n"
+      ]
+    },
     {
       "cell_type": "code",
       "execution_count": null,

diff --git a/docs/latest/_downloads/b53d88bff5e11c5ed50d2a0f66cc5fb1/plot_03_cross_validate.py b/docs/latest/_downloads/b53d88bff5e11c5ed50d2a0f66cc5fb1/plot_03_cross_validate.py
@@ -157,6 +157,22 @@
 # Regression task
 # ^^^^^^^^^^^^^^^
 
+# %%
+# For now, all cross-validation runs store their results in the same place, which might
+# lead to comparing two different models that are actually not comparable (e.g.
+# comparing a regression with a classification).
+# To remedy this, we clear the cross-validation information stored in skore before
+# running another unrelated cross-validation:
+
+# %%
+my_project_gs.delete_item("cross_validation")
+my_project_gs.delete_item("cross_validation_aggregated")
+
+# %%
+# .. note::
+#   Soon, the storage of several unrelated cross-validation runs will be managed
+#   automatically.
+
 # %%
 diabetes = datasets.load_diabetes()
 X = diabetes.data[:150]

diff --git a/docs/latest/_downloads/dafe7022153ade7f6466ced5b7bc6a6d/plot_03_cross_validate.zip b/docs/latest/_downloads/dafe7022153ade7f6466ced5b7bc6a6d/plot_03_cross_validate.zip
diff --git a/docs/latest/_sources/auto_examples/plot_01_getting_started.rst.txt b/docs/latest/_sources/auto_examples/plot_01_getting_started.rst.txt
@@ -792,7 +792,7 @@ project, such as grid search or cross-validation results.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 7.602 seconds)
+   **Total running time of the script:** (0 minutes 7.369 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_01_getting_started.py:

diff --git a/docs/latest/_sources/auto_examples/plot_02_overview_skore_ui.rst.txt b/docs/latest/_sources/auto_examples/plot_02_overview_skore_ui.rst.txt
@@ -459,9 +459,9 @@ Numpy array:
  .. code-block:: none
 
 
-    array([[ 0.89065502,  0.33055527,  0.94646498],
-           [ 0.18747835, -0.33037481, -1.6294029 ],
-           [ 0.58527532, -0.38068824,  0.10142022]])
+    array([[-1.20073514,  1.43585144, -0.60626791],
+           [-0.85039987,  0.11358037,  2.27770174],
+           [-1.33235684, -0.05637076,  1.36512568]])
 
 
 
@@ -513,43 +513,43 @@ Pandas data frame:
       <tbody>
         <tr>
           <th>0</th>
-          <td>0.915014</td>
-          <td>-0.803604</td>
-          <td>-0.231340</td>
-          <td>0.859755</td>
-          <td>-0.009992</td>
+          <td>0.904572</td>
+          <td>-0.296656</td>
+          <td>-0.262589</td>
+          <td>-0.957193</td>
+          <td>0.443695</td>
         </tr>
         <tr>
           <th>1</th>
-          <td>1.004639</td>
-          <td>-2.711596</td>
-          <td>-1.190111</td>
-          <td>-0.023241</td>
-          <td>-0.241200</td>
+          <td>0.206304</td>
+          <td>-1.350691</td>
+          <td>0.383756</td>
+          <td>0.130153</td>
+          <td>0.741917</td>
         </tr>
         <tr>
           <th>2</th>
-          <td>-0.632306</td>
-          <td>0.239900</td>
-          <td>-1.835618</td>
-          <td>1.942414</td>
-          <td>-1.117742</td>
+          <td>-0.655858</td>
+          <td>0.724943</td>
+          <td>0.257821</td>
+          <td>0.716379</td>
+          <td>-0.975402</td>
         </tr>
         <tr>
           <th>3</th>
-          <td>1.173611</td>
-          <td>-0.786674</td>
-          <td>0.119698</td>
-          <td>0.369645</td>
-          <td>-0.075760</td>
+          <td>1.144234</td>
+          <td>0.376084</td>
+          <td>-0.903661</td>
+          <td>-1.449893</td>
+          <td>-0.673322</td>
         </tr>
         <tr>
           <th>4</th>
-          <td>-0.698233</td>
-          <td>-1.253110</td>
-          <td>-0.806476</td>
-          <td>-0.194719</td>
-          <td>0.731890</td>
+          <td>0.904487</td>
+          <td>-1.017765</td>
+          <td>0.184154</td>
+          <td>-0.150802</td>
+          <td>2.026815</td>
         </tr>
       </tbody>
     </table>
@@ -2026,7 +2026,7 @@ Moreover, you can store fitted scikit-learn pipelines:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.520 seconds)
+   **Total running time of the script:** (0 minutes 1.623 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_02_overview_skore_ui.py:

diff --git a/docs/latest/_sources/auto_examples/plot_03_cross_validate.rst.txt b/docs/latest/_sources/auto_examples/plot_03_cross_validate.rst.txt
diff --git a/docs/latest/_sources/index.rst.txt b/docs/latest/_sources/index.rst.txt
@@ -22,7 +22,7 @@ Feedbacks are welcome: please feel free to join our `Discord <http://discord.pro
 
 We are a product team working at `Probabl <https://probabl.ai>`_ and our motto is *Own Your Data Science*.
 
-- License: BSD
+- License: MIT
 - GitHub repository: https://github.com/probabl-ai/skore
 - Discord: http://discord.probabl.ai
 - Status: under development, API is subject to change.
@@ -41,4 +41,4 @@ We are a product team working at `Probabl <https://probabl.ai>`_ and our motto i
    install
    auto_examples/index
    api
-   contributing_link
+   contributing_link
diff --git a/docs/latest/auto_examples/plot_01_getting_started.html b/docs/latest/auto_examples/plot_01_getting_started.html
@@ -1090,7 +1090,7 @@ <h2>Manipulating the skore UI<a class="headerlink" href="#manipulating-the-skore
 <li><p>In the skore UI on the right, you can drag-and-drop items to re-order them, remove items, etc.</p></li>
 </ol>
 <img alt="Getting started with ``skore`` demo" src="https://raw.githubusercontent.com/sylvaincom/sylvaincom.github.io/master/files/probabl/skore/2024_10_31_skore_demo_compressed.gif" />
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 7.602 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 7.369 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-01-getting-started-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/e97c5b0c37bdd66afd2a201f006613dd/plot_01_getting_started.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_01_getting_started.ipynb</span></code></a></p>

diff --git a/docs/latest/auto_examples/plot_02_overview_skore_ui.html b/docs/latest/auto_examples/plot_02_overview_skore_ui.html
@@ -624,9 +624,9 @@ <h2>Storing many kinds of data<a class="headerlink" href="#storing-many-kinds-of
 <span class="n">my_arr</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>array([[ 0.89065502,  0.33055527,  0.94646498],
-       [ 0.18747835, -0.33037481, -1.6294029 ],
-       [ 0.58527532, -0.38068824,  0.10142022]])
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>array([[-1.20073514,  1.43585144, -0.60626791],
+       [-0.85039987,  0.11358037,  2.27770174],
+       [-1.33235684, -0.05637076,  1.36512568]])
 </pre></div>
 </div>
 <p>Pandas data frame:</p>
@@ -664,43 +664,43 @@ <h2>Storing many kinds of data<a class="headerlink" href="#storing-many-kinds-of
   <tbody>
     <tr>
       <th>0</th>
-      <td>0.915014</td>
-      <td>-0.803604</td>
-      <td>-0.231340</td>
-      <td>0.859755</td>
-      <td>-0.009992</td>
+      <td>0.904572</td>
+      <td>-0.296656</td>
+      <td>-0.262589</td>
+      <td>-0.957193</td>
+      <td>0.443695</td>
     </tr>
     <tr>
       <th>1</th>
-      <td>1.004639</td>
-      <td>-2.711596</td>
-      <td>-1.190111</td>
-      <td>-0.023241</td>
-      <td>-0.241200</td>
+      <td>0.206304</td>
+      <td>-1.350691</td>
+      <td>0.383756</td>
+      <td>0.130153</td>
+      <td>0.741917</td>
     </tr>
     <tr>
       <th>2</th>
-      <td>-0.632306</td>
-      <td>0.239900</td>
-      <td>-1.835618</td>
-      <td>1.942414</td>
-      <td>-1.117742</td>
+      <td>-0.655858</td>
+      <td>0.724943</td>
+      <td>0.257821</td>
+      <td>0.716379</td>
+      <td>-0.975402</td>
     </tr>
     <tr>
       <th>3</th>
-      <td>1.173611</td>
-      <td>-0.786674</td>
-      <td>0.119698</td>
-      <td>0.369645</td>
-      <td>-0.075760</td>
+      <td>1.144234</td>
+      <td>0.376084</td>
+      <td>-0.903661</td>
+      <td>-1.449893</td>
+      <td>-0.673322</td>
     </tr>
     <tr>
       <th>4</th>
-      <td>-0.698233</td>
-      <td>-1.253110</td>
-      <td>-0.806476</td>
-      <td>-0.194719</td>
-      <td>0.731890</td>
+      <td>0.904487</td>
+      <td>-1.017765</td>
+      <td>0.184154</td>
+      <td>-0.150802</td>
+      <td>2.026815</td>
     </tr>
   </tbody>
 </table>
@@ -2054,7 +2054,7 @@ <h2>Storing scikit-learn models and pipelines<a class="headerlink" href="#storin
                 (&#x27;lasso&#x27;, Lasso(alpha=2))])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-19" type="checkbox" ><label for="sk-estimator-id-19" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;StandardScaler<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.StandardScaler.html">?<span>Documentation for StandardScaler</span></a></label><div class="sk-toggleable__content fitted"><pre>StandardScaler()</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-20" type="checkbox" ><label for="sk-estimator-id-20" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;Lasso<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.Lasso.html">?<span>Documentation for Lasso</span></a></label><div class="sk-toggleable__content fitted"><pre>Lasso(alpha=2)</pre></div> </div></div></div></div></div></div>
 </div>
 <br />
-<br /><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.520 seconds)</p>
+<br /><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.623 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-02-overview-skore-ui-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/e7cbd7f6fc2c2626a6c20bf80bc30ea7/plot_02_overview_skore_ui.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_02_overview_skore_ui.ipynb</span></code></a></p>