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<!DOCTYPE html>
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<title>Changelog — mvlearn alpha documentation</title>
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<li class="toctree-l3"><a class="reference internal" href="references/decomposition.html#angle-based-joint-and-individual-variation-explained-ajive">Angle-Based Joint and Individual Variation Explained (AJIVE)</a></li>
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<li class="toctree-l2"><a class="reference internal" href="references/model_selection.html">Model Selection</a><ul>
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<li class="toctree-l1 current"><a class="current reference internal" href="#">Changelog</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#version-0-5-0">Version 0.5.0</a></li>
<li class="toctree-l2"><a class="reference internal" href="#version-0-4-1">Version 0.4.1</a></li>
<li class="toctree-l2"><a class="reference internal" href="#version-0-4-0">Version 0.4.0</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#id5">mvlearn.compose</a></li>
<li class="toctree-l3"><a class="reference internal" href="#id13">mvlearn.construct</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#version-0-3-0">Version 0.3.0</a></li>
<li class="toctree-l2"><a class="reference internal" href="#patch-0-2-1">Patch 0.2.1</a></li>
<li class="toctree-l2"><a class="reference internal" href="#version-0-2-0">Version 0.2.0</a></li>
<li class="toctree-l2"><a class="reference internal" href="#version-0-1-0">Version 0.1.0</a></li>
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<li class="toctree-l1"><a class="reference internal" href="license.html">License</a></li>
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<p class="caption" role="heading"><span class="caption-text">Useful Links</span></p>
<ul>
<li class="toctree-l1"><a class="reference external" href="https://github.com/mvlearn/mvlearn">mvlearn @ GitHub</a></li>
<li class="toctree-l1"><a class="reference external" href="https://pypi.org/project/mvlearn/">mvlearn @ PyPI</a></li>
<li class="toctree-l1"><a class="reference external" href="https://github.com/mvlearn/mvlearn/issues">Issue Tracker</a></li>
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<section id="changelog">
<h1>Changelog<a class="headerlink" href="#changelog" title="Permalink to this headline">¶</a></h1>
<p>Change tags (adopted from <a class="reference external" href="https://scikit-learn.org/stable/whats_new/v0.23.html">sklearn</a>):</p>
<ul class="simple">
<li><p><span class="raw-html"><font color="green">[Major Feature]</font></span> : something big that you couldn’t do before.</p></li>
<li><p><span class="raw-html"><font color="green">[Feature]</font></span> : something that you couldn’t do before.</p></li>
<li><p><span class="raw-html"><font color="blue">[Efficiency]</font></span> : an existing feature now may not require as much computation or memory.</p></li>
<li><p><span class="raw-html"><font color="blue">[Enhancement]</font></span> : a miscellaneous minor improvement.</p></li>
<li><p><span class="raw-html"><font color="red">[Fix]</font></span> : something that previously didn’t work as documentated – or according to reasonable expectations – should now work.</p></li>
<li><p><span class="raw-html"><font color="DarkOrange">[API]</font></span> : you will need to change your code to have the same effect in the future; or a feature will be removed in the future.</p></li>
</ul>
<section id="version-0-5-0">
<h2>Version 0.5.0<a class="headerlink" href="#version-0-5-0" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p><span class="raw-html"><font color="red">[Fix]</font></span> <code class="docutils literal notranslate"><span class="pre">CCA</span></code> now only accepts integer arguments for <code class="docutils literal notranslate"><span class="pre">n_components</span></code>, upper bounded by the minimum number of view features. Previously it accepted options that <code class="docutils literal notranslate"><span class="pre">MCCA</span></code> accepted which are only valid for greater than two views. This also had the effect of errors with <code class="docutils literal notranslate"><span class="pre">cca.get_stats</span></code>. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/279">#279</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
<li><p><span class="raw-html"><font color="blue">[Efficiency]</font></span> Removed the package dependency on graspy, now called <a class="reference external" href="https://microsoft.github.io/graspologic/latest/#">graspologic</a>, since graspy is no longer being maintained. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/306">#306</a> by <a class="reference external" href="https://gavinmischler.github.io/">Gavin Mischler</a>.</p></li>
<li><p><span class="raw-html"><font color="DarkOrange">[API]</font></span> Due to the removal of the graspy dependency, the <code class="docutils literal notranslate"><span class="pre">mvlearn.embed.Omnibus</span></code> class has been removed. The same functionality with a similar API can be found in <a class="reference external" href="https://microsoft.github.io/graspologic/latest/reference/reference/embed.html#multiple-graph-embedding">graspologic.embed.OmnibusEmbed</a>.</p></li>
<li><p><span class="raw-html"><font color="red">[Fix]</font></span> An issue in <code class="docutils literal notranslate"><span class="pre">CTClassifier</span></code> where the incorrect samples were being removed from the unlabeled_pool has been fixed. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/304">#304</a> by <a class="reference external" href="https://gavinmischler.github.io/">Gavin Mischler</a>.</p></li>
</ul>
</section>
<section id="version-0-4-1">
<h2>Version 0.4.1<a class="headerlink" href="#version-0-4-1" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p><span class="raw-html"><font color="blue">[Efficiency]</font></span> The 'graspy' package was made an optional dependency in order to reduce the base installation overhead. To use the <cite>Omnibus()</cite> object from <cite>mvlearn.embed</cite>, see the installation guide. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/271">#271</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
</ul>
</section>
<section id="version-0-4-0">
<h2>Version 0.4.0<a class="headerlink" href="#version-0-4-0" title="Permalink to this headline">¶</a></h2>
<p>Updates in this release:</p>
<section id="id5">
<h3><a class="reference external" href="https://github.com/mvlearn/mvlearn/tree/main/mvlearn/compose">mvlearn.compose</a><a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><font color="green">[Major Feature]</font></span> Adds an <code class="docutils literal notranslate"><span class="pre">mvlearn.compose</span></code> module with Merger and Splitter objects to create single views from multiviews and vice versa: <code class="docutils literal notranslate"><span class="pre">ConcatMerger</span></code>, <code class="docutils literal notranslate"><span class="pre">AverageMerger</span></code>, and <code class="docutils literal notranslate"><span class="pre">SimpleSplitter</span></code>. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/228">#228</a>, <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/234">#234</a> by <a class="reference external" href="https://pierreablin.com/">Pierre Ablin</a>.</p></li>
<li><p><span class="raw-html"><font color="green">[Major Feature]</font></span> Adds <code class="docutils literal notranslate"><span class="pre">ViewTransformer</span></code> to apply a single view transformer to each view separately. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/229">#229</a> by <a class="reference external" href="https://pierreablin.com/">Pierre Ablin</a>, <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/263">#263</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
<li><p><span class="raw-html"><font color="green">[Major Feature]</font></span> Adds <code class="docutils literal notranslate"><span class="pre">ViewClassifier</span></code> to apply a single view classifier to each view separately. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/263">#263</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
<li><p><span class="raw-html"><font color="green">[Feature]</font></span> Switches <code class="docutils literal notranslate"><span class="pre">random_subspace_method</span></code> and <code class="docutils literal notranslate"><span class="pre">random_gaussian_projection</span></code> functions to sklearn-compliant estimators <code class="docutils literal notranslate"><span class="pre">RandomSubspaceMethod</span></code> and <code class="docutils literal notranslate"><span class="pre">RandomGaussianProjection</span></code>. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/263">#263</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
<li><p><span class="raw-html"><font color="DarkOrange">[API]</font></span> The <code class="docutils literal notranslate"><span class="pre">mvlearn.construct</span></code> module was merged into <code class="docutils literal notranslate"><span class="pre">mvlearn.compose</span></code> due to overlapping functionality. Any imports statements change accordingly. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/258">#258</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
</ul>
</section>
<section id="id13">
<h3><a class="reference external" href="https://github.com/mvlearn/mvlearn/tree/main/mvlearn/construct">mvlearn.construct</a><a class="headerlink" href="#id13" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><font color="DarkOrange">[API]</font></span> The <code class="docutils literal notranslate"><span class="pre">mvlearn.construct</span></code> module was merged into <code class="docutils literal notranslate"><span class="pre">mvlearn.compose</span></code> due to overlapping functionality and no longer exists. Any imports statements change accordingly. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/258">#258</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
</ul>
</section>
<section id="id15">
<h3><a class="reference external" href="https://github.com/mvlearn/mvlearn/tree/main/mvlearn/decomposition">mvlearn.decomposition</a><a class="headerlink" href="#id15" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><font color="green">[Feature]</font></span> Adds <code class="docutils literal notranslate"><span class="pre">GroupICA</span></code> and <code class="docutils literal notranslate"><span class="pre">GroupPCA</span></code>. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/225">#225</a> by <a class="reference external" href="https://pierreablin.com/">Pierre Ablin</a> and <a class="reference external" href="https://github.com/hugorichard">Hugo Richard</a>.</p></li>
</ul>
</section>
<section id="id17">
<h3><a class="reference external" href="https://github.com/mvlearn/mvlearn/tree/main/mvlearn/embed">mvlearn.embed</a><a class="headerlink" href="#id17" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><font color="green">[Feature]</font></span> Adds Multi CCA (<code class="docutils literal notranslate"><span class="pre">MCCA</span></code>) and Kernel MCCA (<code class="docutils literal notranslate"><span class="pre">KMCCA</span></code>) for two or more views. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/249">#249</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a> and <a class="reference external" href="https://idc9.github.io/">Iain Carmichael</a>.</p></li>
<li><p><span class="raw-html"><font color="green">[Feature]</font></span> Adds CCA, MCCA which requires 2 views but has a variety of interpretable statistics. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/251">#261</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
<li><p><span class="raw-html"><font color="DarkOrange">[API]</font></span> Removes KCCA and moves its functionallity into KMCCA. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/251">#261</a> by <a class="reference external" href="http://rflperry.github.io/">Ronan Perry</a>.</p></li>
</ul>
</section>
<section id="id21">
<h3><a class="reference external" href="https://github.com/mvlearn/mvlearn/tree/main/mvlearn/model_selection">mvlearn.model_selection</a><a class="headerlink" href="#id21" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><font color="green">[Major Feature]</font></span> Adds an <code class="docutils literal notranslate"><span class="pre">model_selection</span></code> module with multiview cross validation. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/234">#234</a> by <a class="reference external" href="https://pierreablin.com/">Pierre Ablin</a>.</p></li>
<li><p><span class="raw-html"><font color="green">[Feature]</font></span> Adds the function <code class="docutils literal notranslate"><span class="pre">model_selection.train_test_split</span></code> to wrap that of <a class="reference external" href="https://scikit-learn.org/">sklearn <scikit-learn</a> for multiview data or items. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/174">#174</a> by <a class="reference external" href="https://github.com/achang63">Alexander Chang</a> and <a class="reference external" href="https://gavinmischler.github.io/">Gavin Mischler</a>.</p></li>
</ul>
</section>
<section id="id24">
<h3><a class="reference external" href="https://github.com/mvlearn/mvlearn/tree/main/mvlearn/utils">mvlearn.utils</a><a class="headerlink" href="#id24" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<li><p><span class="raw-html"><font color="blue">[Enhancement]</font></span> Adds a parameter to utils.check_Xs so that the function also returns the dimensions (n_views, n_samples, n_features) of the input dataset. <a class="reference external" href="https://github.com/mvlearn/mvlearn/pull/235">#235</a> by <a class="reference external" href="https://pierreablin.com/">Pierre Ablin</a>.</p></li>
</ul>
</section>
</section>
<section id="version-0-3-0">
<h2>Version 0.3.0<a class="headerlink" href="#version-0-3-0" title="Permalink to this headline">¶</a></h2>
<p>Updates in this release:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">cotraining</span></code> module changed to <code class="docutils literal notranslate"><span class="pre">semi_supervised</span></code>.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">factorization</span></code> module changed to <code class="docutils literal notranslate"><span class="pre">decomposition</span></code>.</p></li>
<li><p>A new class within the <code class="docutils literal notranslate"><span class="pre">semi_supervised</span></code> module, <code class="docutils literal notranslate"><span class="pre">CTRegressor</span></code>, and regression tool for 2-view semi-supervised learning, following the cotraining framework.</p></li>
<li><p>Three multiview ICA methods added: MultiviewICA, GroupICA, PermICA with <code class="docutils literal notranslate"><span class="pre">python-picard</span></code> dependency.</p></li>
<li><p>Added parallelizability to GCCA using joblib and added <code class="docutils literal notranslate"><span class="pre">partial_fit</span></code> function to handle streaming or large data.</p></li>
<li><p>Adds a function (get_stats()) to perform statistical tests within the <code class="docutils literal notranslate"><span class="pre">embed.KCCA</span></code> class so that canonical correlations and canonical variates can be robustly. assessed for significance. See the documentation in Reference for more details.</p></li>
<li><p>Adds ability to select which views to return from the UCI multiple features dataset loader, <code class="docutils literal notranslate"><span class="pre">datasets.UCI_multifeature</span></code>.</p></li>
<li><p>API enhancements including base classes for each module and algorithm type, allowing for greater flexibility to extend <code class="docutils literal notranslate"><span class="pre">mvlearn</span></code>.</p></li>
<li><p>Internals of <code class="docutils literal notranslate"><span class="pre">SplitAE</span></code> changed to snake case to fit with the rest of the package.</p></li>
<li><p>Fixes a bug which prevented the <code class="docutils literal notranslate"><span class="pre">visualize.crossviews_plot</span></code> from plotting when each view only has a single feature.</p></li>
<li><p>Changes to the <code class="docutils literal notranslate"><span class="pre">mvlearn.datasets.gaussian_mixture.GaussianMixture</span></code> parameters to better mimic sklearn's datasets.</p></li>
<li><p>Fixes a bug with printing error messages in a few classes.</p></li>
</ul>
</section>
<section id="patch-0-2-1">
<h2>Patch 0.2.1<a class="headerlink" href="#patch-0-2-1" title="Permalink to this headline">¶</a></h2>
<p>Fixed missing <code class="docutils literal notranslate"><span class="pre">__init__.py</span></code> file in the <code class="docutils literal notranslate"><span class="pre">ajive_utils</span></code> submodule.</p>
</section>
<section id="version-0-2-0">
<h2>Version 0.2.0<a class="headerlink" href="#version-0-2-0" title="Permalink to this headline">¶</a></h2>
<p>Updates in this release:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">MVMDS</span></code> can now also accept distance matrices as input, rather than only views of data with samples and features</p></li>
<li><p>A new clustering algorithm, <code class="docutils literal notranslate"><span class="pre">CoRegMultiviewSpectralClustering</span></code> - co-regularized multi-view spectral clustering functionality</p></li>
<li><p>Some attribute names slightly changed for more intuitive use in <code class="docutils literal notranslate"><span class="pre">DCCA</span></code>, <code class="docutils literal notranslate"><span class="pre">KCCA</span></code>, <code class="docutils literal notranslate"><span class="pre">MVMDS</span></code>, <code class="docutils literal notranslate"><span class="pre">CTClassifier</span></code></p></li>
<li><p>Option to use an Incomplete Cholesky Decomposition method for <code class="docutils literal notranslate"><span class="pre">KCCA</span></code> to reduce up computation times</p></li>
<li><p>A new module, <code class="docutils literal notranslate"><span class="pre">factorization</span></code>, containing the <code class="docutils literal notranslate"><span class="pre">AJIVE</span></code> algorithm - angle-based joint and individual variance explained</p></li>
<li><p>Fixed issue where signal dimensions of noise were dependent in the GaussianMixtures class</p></li>
<li><p>Added a dependecy to <code class="docutils literal notranslate"><span class="pre">joblib</span></code> to enable parallel clustering implementation</p></li>
<li><p>Removed the requirements for <code class="docutils literal notranslate"><span class="pre">torchvision</span></code> and <code class="docutils literal notranslate"><span class="pre">pillow</span></code>, since they are only used in tutorials</p></li>
</ul>
</section>
<section id="version-0-1-0">
<h2>Version 0.1.0<a class="headerlink" href="#version-0-1-0" title="Permalink to this headline">¶</a></h2>
<p>We’re happy to announce the first major stable version of <code class="docutils literal notranslate"><span class="pre">mvlearn</span></code>.
This version includes multiple new algorithms, more utility functions, as well as significant enhancements to the documentation. Here are some highlights of the big updates.</p>
<ul class="simple">
<li><p>Deep CCA, (<code class="docutils literal notranslate"><span class="pre">DCCA</span></code>) in the <code class="docutils literal notranslate"><span class="pre">embed</span></code> module</p></li>
<li><p>Updated <code class="docutils literal notranslate"><span class="pre">KCCA</span></code> with multiple kernels</p></li>
<li><p>Synthetic multi-view dataset generator class, <code class="docutils literal notranslate"><span class="pre">GaussianMixture</span></code>, in the <code class="docutils literal notranslate"><span class="pre">datasets</span></code> module</p></li>
<li><p>A new module, <code class="docutils literal notranslate"><span class="pre">plotting</span></code>, which includes functions for visualizing multi-view data, such as <code class="docutils literal notranslate"><span class="pre">crossviews_plot</span></code> and <code class="docutils literal notranslate"><span class="pre">quick_visualize</span></code></p></li>
<li><p>More detailed tutorial notebooks for all algorithms</p></li>
</ul>
<p>Additionally, mvlearn now makes the <code class="docutils literal notranslate"><span class="pre">torch</span></code> and <code class="docutils literal notranslate"><span class="pre">tqdm</span></code> dependencies optional, so users who don’t need the DCCA or SplitAE functionality do not have to import such a large package. <strong>Note</strong> this is only the case for installing with pip. Installing from <code class="docutils literal notranslate"><span class="pre">conda</span></code> includes these dependencies automatically. To install the full version of mvlearn with <code class="docutils literal notranslate"><span class="pre">torch</span></code> and <code class="docutils literal notranslate"><span class="pre">tqdm</span></code> from pip, you must include the optional torch in brackets:</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">pip3</span> <span class="n">install</span> <span class="n">mvlearn</span><span class="p">[</span><span class="n">torch</span><span class="p">]</span>
</pre></div>
</div>
</div></blockquote>
<p>or</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">pip3</span> <span class="n">install</span> <span class="o">--</span><span class="n">upgrade</span> <span class="n">mvlearn</span><span class="p">[</span><span class="n">torch</span><span class="p">]</span>
</pre></div>
</div>
</div></blockquote>
<p>To install <strong>without</strong> <code class="docutils literal notranslate"><span class="pre">torch</span></code>, do:</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">pip3</span> <span class="n">install</span> <span class="n">mvlearn</span>
</pre></div>
</div>
</div></blockquote>
<p>or</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">pip3</span> <span class="n">install</span> <span class="o">--</span><span class="n">upgrade</span> <span class="n">mvlearn</span>
</pre></div>
</div>
</div></blockquote>
</section>
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