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<li><a class="reference internal" href="#">News</a><ul>
<li><a class="reference internal" href="#version-0-1-2-released">[04/09/2022] Version 0.1.2 released!</a></li>
<li><a class="reference internal" href="#version-0-1-1-released">[10/04/2022] Version 0.1.1 released!</a></li>
<li><a class="reference internal" href="#version-0-1-0-released">[18/05/2020] Version 0.1.0 released!</a></li>
<li><a class="reference internal" href="#version-0-0-2-released">[04/11/2019] Version 0.0.2 released!</a></li>
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<li><a class="reference internal" href="#version-0-1-2-released">[04/09/2022] Version 0.1.2 released!</a></li>
<li><a class="reference internal" href="#version-0-1-1-released">[10/04/2022] Version 0.1.1 released!</a></li>
<li><a class="reference internal" href="#version-0-1-0-released">[18/05/2020] Version 0.1.0 released!</a></li>
<li><a class="reference internal" href="#version-0-0-2-released">[04/11/2019] Version 0.0.2 released!</a></li>
<li><a class="reference internal" href="#version-0-0-1-released">[01/08/2019] Version 0.0.1 released!</a></li>
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<section id="news">
<span id="id1"></span><h1>News<a class="headerlink" href="#news" title="Permalink to this headline">¶</a></h1>
<section id="version-0-1-2-released">
<h2>[04/09/2022] Version 0.1.2 released!<a class="headerlink" href="#version-0-1-2-released" title="Permalink to this headline">¶</a></h2>
<p>Today we release a minor update fixing segmentation and occlusion bugs.</p>
<p>The changelog summarises the bugs fixed in this release:
<a class="reference internal" href="changelog.html#changelog-0-1-2"><span class="std std-ref">0.1.2 (04/09/2022)</span></a>.</p>
</section>
<section id="version-0-1-1-released">
<h2>[10/04/2022] Version 0.1.1 released!<a class="headerlink" href="#version-0-1-1-released" title="Permalink to this headline">¶</a></h2>
<p>Today we release an incremental update focused on surrogate <em>image</em> explainers.
This release comes with functionality for image segmentation, image occlusion
and a bLIMEy implementation of image LIME, as well as a simple binary data
augmentation technique and submodular pick.</p>
<p>The changelog summarises the functionality added with this release:
<a class="reference internal" href="changelog.html#changelog-0-1-1"><span class="std std-ref">0.1.1 (10/04/2022)</span></a>.</p>
<p>Next up, surrogate explainability for text data.</p>
</section>
<section id="version-0-1-0-released">
<h2>[18/05/2020] Version 0.1.0 released!<a class="headerlink" href="#version-0-1-0-released" title="Permalink to this headline">¶</a></h2>
<p>Today we release an incremental update focused on surrogate explainers.
This release coincides with publication of a <a class="reference external" href="https://joss.theoj.org/papers/10.21105/joss.01904">paper</a>
describing FAT Forensic in The Journal of Open Source Software (JOSS).
The changelog summarises the functionality added with this release:
<a class="reference internal" href="changelog.html#changelog-0-1-0"><span class="std std-ref">0.1.0 (18/05/2020)</span></a>.</p>
<p>Next up, surrogate explainability for image and text data.</p>
</section>
<section id="version-0-0-2-released">
<h2>[04/11/2019] Version 0.0.2 released!<a class="headerlink" href="#version-0-0-2-released" title="Permalink to this headline">¶</a></h2>
<p>Today we release an incremental update focused on surrogate explainability of
black-box models for tabular data – a collection of techniques and algorithms
that we call <em>build LIME yourself</em> (<strong>bLIMEy</strong>). The changelog summarises the
functionality added with this release: <a class="reference internal" href="changelog.html#changelog-0-0-2"><span class="std std-ref">0.0.2 (04/11/2019)</span></a>.</p>
<p>This code release comes with a new <em>how-to</em> guide:
<a class="reference internal" href="how_to/transparency/tabular-surrogates.html#how-to-tabular-surrogates"><span class="std std-ref">How to build LIME yourself (bLIMEy) – Surrogate Tabular Explainers</span></a>. We have also added one more code example –
<a class="reference internal" href="sphinx_gallery_auto/transparency/xmpl_transparency_tree.html#sphx-glr-sphinx-gallery-auto-transparency-xmpl-transparency-tree-py"><span class="std std-ref">Using a Surrogate Tree Explainer</span></a> –
and updated the LIME code example
(<a class="reference internal" href="sphinx_gallery_auto/transparency/xmpl_transparency_lime.html#sphx-glr-sphinx-gallery-auto-transparency-xmpl-transparency-lime-py"><span class="std std-ref">Using LIME Explainer</span></a>)
to use the bLIMEy implementation of LIME
(<a class="reference internal" href="generated/fatf.transparency.predictions.surrogate_explainers.TabularBlimeyLime.html#fatf.transparency.predictions.surrogate_explainers.TabularBlimeyLime" title="fatf.transparency.predictions.surrogate_explainers.TabularBlimeyLime"><code class="xref py py-class docutils literal notranslate"><span class="pre">fatf.transparency.predictions.surrogate_explainers.TabularBlimeyLime</span></code></a>)
instead. The “<a class="reference internal" href="tutorials/prediction-explainability.html#tutorials-prediction-explainability"><span class="std std-ref">Explaining Machine Learning Predictions: LIME and Counterfactuals</span></a>” tutorial has also
been updated to use bLIMEy instead of LIME.</p>
<p>Surrogate explainability for image and text data is coming soon so stay tuned.</p>
</section>
<section id="version-0-0-1-released">
<h2>[01/08/2019] Version 0.0.1 released!<a class="headerlink" href="#version-0-0-1-released" title="Permalink to this headline">¶</a></h2>
<p>Today we release our first public version of the FAT Forensics package. To
familiarise yourself with the FAT Forensics Python package make sure to check
out our <a class="reference internal" href="getting_started/index.html#getting-started"><span class="std std-ref">Getting Started</span></a> page. The changelog summarises functionality
of this release: <a class="reference internal" href="changelog.html#changelog-0-0-1"><span class="std std-ref">0.0.1 (01/08/2019)</span></a>.</p>
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