✨ [Feature request] - Add Seshat API example notebook showing prediction of complexity characteristics

[edwardchalstrey1]

Description of Improvement

Initial Hypotheses/ideas:

• Predict something, use sklearn or another ML package.
• Can we predict whether a polity is likely to have variable A, given the presence of variables B, C & D

After having read this paper:

• They fitted a predictive model based on the Complexity Characteristics (CCs) of most of the world regions (training set), then were able to use it to predict the CCs of North America (test set)
• Their most useful Principal Component ("PC") called "PC1" (unsure how calculated) shows general increase across polities or regions over time
• "The tight relationships between different CCs provide support for the idea that there are functional relationships between these characteristics that cause them to coevolve"

Notebook idea: Rather than replicating the Principal Component analysis, which Matilda is doing, a simpler ML notebook could involve:

1. loading the data for several CCs that the paper says are linked
2. Training a model to predict one CC based on others
3. Evaluating the performance of the model

Dependencies

No response

Technical Notes

• Because of the way the database/api is set up, it's very hard to get for a single polity, or set of polities, all the values of all the variables

Definition of Done

• The feature has been developed on a feature branch.
• A pull request has been created for the feature branch to be merged into the main branch.