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‎docs/_static/doctools.js

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‎docs/contents.html

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<li class="toctree-l2"><a class="reference internal" href="generated/adapt.parameter_based.RegularTransferNN.html">RegularTransferNN</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/adapt.parameter_based.FineTuning.html">FineTuning</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/adapt.parameter_based.TransferTreeClassifier.html">TransferTreeClassifier</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/adapt.parameter_based.TransferForestClassifier.html">TransferForestClassifier</a></li>
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<li class="toctree-l1"><a class="reference internal" href="#adapt-metrics">Metrics</a><ul>
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<p class="rubric">Methods</p>
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<td><p>FineTuning : finetunes pretrained networks on target data.</p></td>
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<tr class="row-odd"><td><p><a class="reference internal" href="generated/adapt.parameter_based.TransferTreeClassifier.html#adapt.parameter_based.TransferTreeClassifier" title="adapt.parameter_based.TransferTreeClassifier"><code class="xref py py-obj docutils literal notranslate"><span class="pre">parameter_based.TransferTreeClassifier</span></code></a>([...])</p></td>
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<td><p>TBA</p></td>
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<td><p>TransferTreeClassifier: Modify a source Decision tree on a target dataset.</p></td>
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<tr class="row-even"><td><p><a class="reference internal" href="generated/adapt.parameter_based.TransferForestClassifier.html#adapt.parameter_based.TransferForestClassifier" title="adapt.parameter_based.TransferForestClassifier"><code class="xref py py-obj docutils literal notranslate"><span class="pre">parameter_based.TransferForestClassifier</span></code></a>([...])</p></td>
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<section id="adapt-metrics-metrics">
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<span id="adapt-metrics"></span><h2><a class="reference internal" href="#adapt-metrics"><span class="std std-ref">adapt.metrics</span></a>: Metrics<a class="headerlink" href="#adapt-metrics-metrics" title="Permalink to this headline"></a></h2>
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<p>This module contains functions to compute adaptation metrics.</p>
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<span id="adapt-utils"></span><h2><a class="reference internal" href="#adapt-utils"><span class="std std-ref">adapt.utils</span></a>: Utility Functions<a class="headerlink" href="#adapt-utils-utility-functions" title="Permalink to this headline"></a></h2>
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<p>This module contains utility functions used in the previous modules.</p>
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‎docs/examples/Classification.html

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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.RegularTransferNN.html">RegularTransferNN</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.FineTuning.html">FineTuning</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.TransferTreeClassifier.html">TransferTreeClassifier</a></li>
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<section id="Classification">
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<h1>Classification<a class="headerlink" href="#Classification" title="Permalink to this headline"></a></h1>
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<div class="btn btn-notebook" role="button"><p><img alt="a966f76b77f24009aa977763ca649bb9" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1ANQUix9Y6V4RXu-vAaCFGmU979d5m4bO?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="4335e175433742a2ad920bb842514876" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Classification.ipynb">View on GitHub</a></p>
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<div class="btn btn-notebook" role="button"><p><img alt="8273b5f76d024ec6a6fcb2ab2aebdbe4" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1ANQUix9Y6V4RXu-vAaCFGmU979d5m4bO?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="aa92149bf8224e3db01a5eb7c66fbfa8" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Classification.ipynb">View on GitHub</a></p>
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</div><p>You will find here the application of DA methods from the ADAPT package on a simple two dimensional DA classification problem.</p>
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<p>First we import packages needed in the following. We will use <code class="docutils literal notranslate"><span class="pre">matplotlib</span> <span class="pre">Animation</span></code> tools in order to get a visual understanding of the mselected methods:</p>
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‎docs/examples/Multi_fidelity.html

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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.FineTuning.html">FineTuning</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.TransferTreeClassifier.html">TransferTreeClassifier</a></li>
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<section id="Multi-Fidelity">
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<h1>Multi-Fidelity<a class="headerlink" href="#Multi-Fidelity" title="Permalink to this headline"></a></h1>
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<div class="btn btn-notebook" role="button"><p><img alt="30ffe81bd05f45ea916075bb1f6386f1" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1Cc9TVY_Tl_boVzZDNisQnqe6Qx78svqe?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="d04db52ebb1f471a93a750710c96c5a7" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Multi_fidelity.ipynb">View on GitHub</a></p>
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<div class="btn btn-notebook" role="button"><p><img alt="5c37e0cb0ad6424498510522707778b7" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1Cc9TVY_Tl_boVzZDNisQnqe6Qx78svqe?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="a0b0bb598cc04871a485e6428870fcdb" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Multi_fidelity.ipynb">View on GitHub</a></p>
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</div><p>The following example is a 1D regression multi-fidelity issue. Blue points are low fidelity observations and orange points are high fidelity observations. The goal is to use both datasets to learn the task on the [0, 1] interval.</p>
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<p>To tackle this challenge, we use here the parameter-based method: <a class="reference external" href="#RegularTransferNN">RegularTransferNN</a></p>
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‎docs/examples/Regression.html

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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.RegularTransferNN.html">RegularTransferNN</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.FineTuning.html">FineTuning</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.TransferTreeClassifier.html">TransferTreeClassifier</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.TransferForestClassifier.html">TransferForestClassifier</a></li>
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<section id="Toy-Regression">
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<h1>Toy Regression<a class="headerlink" href="#Toy-Regression" title="Permalink to this headline"></a></h1>
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<div class="btn btn-notebook" role="button"><p><img alt="b653644c0aeb42a582c3f958545c1ad0" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1adhqoV6b0uEavLDmMfkiwtRjam0DrXux?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="0048eac286214a80b6c3a06c47700b07" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Regression.ipynb">View on GitHub</a></p>
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<div class="btn btn-notebook" role="button"><p><img alt="24f5f2e739b444989256c3c562f8b73f" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1adhqoV6b0uEavLDmMfkiwtRjam0DrXux?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="d6b14d0fd0c248da88ca9a4a8df02df8" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Regression.ipynb">View on GitHub</a></p>
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</div><p>You will find here the application of DA methods from the ADAPT package on a simple one dimensional DA regression problem.</p>
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<p>First we import packages needed in the following. We will use <code class="docutils literal notranslate"><span class="pre">matplotlib</span> <span class="pre">Animation</span></code> tools in order to get a visual understanding of the selected methods:</p>
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‎docs/examples/Rotation.html

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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.FineTuning.html">FineTuning</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.TransferTreeClassifier.html">TransferTreeClassifier</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../generated/adapt.parameter_based.TransferForestClassifier.html">TransferForestClassifier</a></li>
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<section id="Rotation">
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<h1>Rotation<a class="headerlink" href="#Rotation" title="Permalink to this headline"></a></h1>
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<div class="btn btn-notebook" role="button"><p><img alt="3f548eeb62484142857cf0d514cc73f7" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1XePW12UF80PKzvLu9cyRJKWQoZIxk_J2?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="51599fe3c6584045a915b0fe378ac67b" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Rotation.ipynb">View on GitHub</a></p>
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<div class="btn btn-notebook" role="button"><p><img alt="d070dd883a0740a69ea6a3a324092a24" src="../_images/colab_logo_32px.png" /> <a class="reference external" href="https://colab.research.google.com/drive/1XePW12UF80PKzvLu9cyRJKWQoZIxk_J2?usp=sharing">Run in Google Colab</a></p>
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</div><div class="btn btn-notebook" role="button"><p><img alt="5af0949e32964106a7d1530f5fba2cda" src="../_images/github_logo_32px.png" /> <a class="reference external" href="https://github.com/adapt-python/notebooks/blob/d0364973c642ea4880756cef4e9f2ee8bb5e8495/Rotation.ipynb">View on GitHub</a></p>
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<div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[2]:
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