for those of us trying to suss out the implications of this, I offer:
https://en.wikipedia.org/wiki/Shapley_value
I'm not clear on a number of things Jochen:
1. The Shapley values implies an iterated/cooperative model?
2. I see how the "training set" from post WWI Europe might be used in
this context.
3. How do your assumptions about Trump-era America fit in?
1. Is the assumption that post WWI (hidden) conditions in Europe
are similar enough to contemporary Global conditions?
I'm probably missing something (a lot)?
- Steve
On 7/15/22 2:06 PM, Jochen Fromm wrote:
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.
No big data or deep learning, just a small neural network based on
scikit-learn (no Tensorflow, Keras, or Pytorch). Juypter notebook here:
https://nbviewer.org/github/JochenFromm/JupyterNotebooks/blob/master/ModelingFascism.ipynb
-J.
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