Max-cut and Hierarchical Learning #78
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ajrazander
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dongreenberg and
woodsp-ibm
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Summary
The Max-cut_vs_k_means.ipynb notebook implements k-means and the max-cut problem solved by QAOA to cluster data. The max-cut problem solved by QAOA is effectively a binary classifier. The Max-cut_2+_divisive_clustering.ipynb notebook is a sequel tutorial where 2+ clustering groups are formed by applying the same max-cut problem solved by QAOA approach but in a divisive hierarchical scheme.
Details and comments
These are the first tutorials I have contributed, and first time I have done a pull request. I would appreciate feedback so they become as useful as possible. I did see the max-cut tutorial under optimization. However, this has an AI focus--particularly in the second notebook. It also expands to hierarchical analysis which is not covered in any notebook yet.