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    <title>PyPI recent updates for fair-trees</title>
    <link>https://pypi.org/project/fair-trees/</link>
    <description>Recent updates to the Python Package Index for fair-trees</description>
    <language>en</language>    <item>
      <title>3.1.9</title>
      <link>https://pypi.org/project/fair-trees/3.1.9/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 23:36:38 GMT</pubDate>
    </item>    <item>
      <title>3.1.8</title>
      <link>https://pypi.org/project/fair-trees/3.1.8/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 23:13:01 GMT</pubDate>
    </item>    <item>
      <title>3.1.7</title>
      <link>https://pypi.org/project/fair-trees/3.1.7/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 19:02:20 GMT</pubDate>
    </item>    <item>
      <title>3.1.6</title>
      <link>https://pypi.org/project/fair-trees/3.1.6/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 18:54:26 GMT</pubDate>
    </item>    <item>
      <title>3.1.5</title>
      <link>https://pypi.org/project/fair-trees/3.1.5/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 18:47:22 GMT</pubDate>
    </item>    <item>
      <title>3.1.4</title>
      <link>https://pypi.org/project/fair-trees/3.1.4/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 18:32:06 GMT</pubDate>
    </item>    <item>
      <title>3.1.3</title>
      <link>https://pypi.org/project/fair-trees/3.1.3/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 18:20:13 GMT</pubDate>
    </item>    <item>
      <title>3.1.2</title>
      <link>https://pypi.org/project/fair-trees/3.1.2/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 17:48:13 GMT</pubDate>
    </item>    <item>
      <title>3.1.1</title>
      <link>https://pypi.org/project/fair-trees/3.1.1/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 15:40:41 GMT</pubDate>
    </item>    <item>
      <title>3.1.0</title>
      <link>https://pypi.org/project/fair-trees/3.1.0/</link>
      <description>Fairness-aware decision tree and random forest classifiers</description>
      <pubDate>Fri, 20 Feb 2026 15:19:34 GMT</pubDate>
    </item>    <item>
      <title>2.6.6</title>
      <link>https://pypi.org/project/fair-trees/2.6.6/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 30 Apr 2025 15:35:44 GMT</pubDate>
    </item>    <item>
      <title>2.6.5</title>
      <link>https://pypi.org/project/fair-trees/2.6.5/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 16 Apr 2025 22:29:29 GMT</pubDate>
    </item>    <item>
      <title>2.6.4</title>
      <link>https://pypi.org/project/fair-trees/2.6.4/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 01 Apr 2025 15:41:06 GMT</pubDate>
    </item>    <item>
      <title>2.6.3</title>
      <link>https://pypi.org/project/fair-trees/2.6.3/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 01 Apr 2025 15:29:54 GMT</pubDate>
    </item>    <item>
      <title>2.6.2</title>
      <link>https://pypi.org/project/fair-trees/2.6.2/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 01 Apr 2025 15:23:33 GMT</pubDate>
    </item>    <item>
      <title>2.6.1</title>
      <link>https://pypi.org/project/fair-trees/2.6.1/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 01 Apr 2025 14:46:05 GMT</pubDate>
    </item>    <item>
      <title>2.4.9</title>
      <link>https://pypi.org/project/fair-trees/2.4.9/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 10 Apr 2024 14:22:08 GMT</pubDate>
    </item>    <item>
      <title>2.4.8</title>
      <link>https://pypi.org/project/fair-trees/2.4.8/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 10 Apr 2024 14:16:08 GMT</pubDate>
    </item>    <item>
      <title>2.4.7</title>
      <link>https://pypi.org/project/fair-trees/2.4.7/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 10 Apr 2024 14:13:46 GMT</pubDate>
    </item>    <item>
      <title>2.4.6</title>
      <link>https://pypi.org/project/fair-trees/2.4.6/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 10 Apr 2024 14:05:48 GMT</pubDate>
    </item>    <item>
      <title>2.4.5</title>
      <link>https://pypi.org/project/fair-trees/2.4.5/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 10 Apr 2024 13:44:34 GMT</pubDate>
    </item>    <item>
      <title>2.4.4</title>
      <link>https://pypi.org/project/fair-trees/2.4.4/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Wed, 10 Apr 2024 13:26:16 GMT</pubDate>
    </item>    <item>
      <title>2.4.3</title>
      <link>https://pypi.org/project/fair-trees/2.4.3/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 17:32:26 GMT</pubDate>
    </item>    <item>
      <title>2.4.2</title>
      <link>https://pypi.org/project/fair-trees/2.4.2/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 17:27:09 GMT</pubDate>
    </item>    <item>
      <title>2.4.1</title>
      <link>https://pypi.org/project/fair-trees/2.4.1/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 16:58:26 GMT</pubDate>
    </item>    <item>
      <title>2.3.10</title>
      <link>https://pypi.org/project/fair-trees/2.3.10/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 16:18:38 GMT</pubDate>
    </item>    <item>
      <title>2.3.9</title>
      <link>https://pypi.org/project/fair-trees/2.3.9/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 16:13:18 GMT</pubDate>
    </item>    <item>
      <title>2.3.8</title>
      <link>https://pypi.org/project/fair-trees/2.3.8/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 16:09:20 GMT</pubDate>
    </item>    <item>
      <title>2.3.7</title>
      <link>https://pypi.org/project/fair-trees/2.3.7/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 16:06:52 GMT</pubDate>
    </item>    <item>
      <title>2.3.5</title>
      <link>https://pypi.org/project/fair-trees/2.3.5/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 16:00:22 GMT</pubDate>
    </item>    <item>
      <title>2.3.4</title>
      <link>https://pypi.org/project/fair-trees/2.3.4/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 15:57:53 GMT</pubDate>
    </item>    <item>
      <title>2.3.3</title>
      <link>https://pypi.org/project/fair-trees/2.3.3/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 15:45:21 GMT</pubDate>
    </item>    <item>
      <title>2.3.2</title>
      <link>https://pypi.org/project/fair-trees/2.3.2/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 15:39:19 GMT</pubDate>
    </item>    <item>
      <title>2.3.1</title>
      <link>https://pypi.org/project/fair-trees/2.3.1/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 15:23:53 GMT</pubDate>
    </item>    <item>
      <title>2.3</title>
      <link>https://pypi.org/project/fair-trees/2.3/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 14:17:10 GMT</pubDate>
    </item>    <item>
      <title>2.2</title>
      <link>https://pypi.org/project/fair-trees/2.2/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 14:12:17 GMT</pubDate>
    </item>    <item>
      <title>2.1</title>
      <link>https://pypi.org/project/fair-trees/2.1/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 14:04:31 GMT</pubDate>
    </item>    <item>
      <title>2.0</title>
      <link>https://pypi.org/project/fair-trees/2.0/</link>
      <description>This package learns fair decision tree classifiers which can then be bagged into fair random forests, following the scikit-learn API standards.</description>
<author>apbarata@gmail.com</author>      <pubDate>Tue, 09 Apr 2024 13:48:20 GMT</pubDate>
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