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<p>for those of us trying to suss out the implications of this, I
offer:</p>
<p> <a class="moz-txt-link-freetext" href="https://en.wikipedia.org/wiki/Shapley_value">https://en.wikipedia.org/wiki/Shapley_value</a></p>
<p>I'm not clear on a number of things Jochen:</p>
<ol>
<li>The Shapley values implies an iterated/cooperative model?</li>
<li>I see how the "training set" from post WWI Europe might be
used in this context.</li>
<li>How do your assumptions about Trump-era America fit in? <br>
</li>
<ol>
<li>Is the assumption that post WWI (hidden) conditions in
Europe are similar enough to contemporary Global conditions?</li>
</ol>
</ol>
<p>I'm probably missing something (a lot)?</p>
<p>- Steve<br>
</p>
<div class="moz-cite-prefix">On 7/15/22 2:06 PM, Jochen Fromm wrote:<br>
</div>
<blockquote type="cite"
cite="mid:202207152006.26FK6vVL069721@ame4.swcp.com">
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<div dir="auto">Today after work I've tried to built a small and
simple machine learning model to predict fascism, based on 6 or
7 fundamental features. Using Shapley values we can see which
feature contributes the most to the outbreak of fascism. If I
enter values which fit to the US under Trump the model indeed
predicts a form of authoritarianism.</div>
<div dir="auto"><br>
</div>
<div dir="auto">No big data or deep learning, just a small neural
network based on scikit-learn (no Tensorflow, Keras, or
Pytorch). Juypter notebook here:</div>
<div dir="auto"><a class="moz-txt-link-freetext" href="https://nbviewer.org/github/JochenFromm/JupyterNotebooks/blob/master/ModelingFascism.ipynb">https://nbviewer.org/github/JochenFromm/JupyterNotebooks/blob/master/ModelingFascism.ipynb</a></div>
<div dir="auto"><br>
</div>
<div dir="auto">-J.</div>
<div dir="auto"><br>
</div>
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