multiple objective support
In last webinar I had asked about potential solutions to support balancing across multiple objectives and speaker ran out of time before answering. It occurs to me that there is a lot of interesting prior work from classical learning domain associated with balancing between multiple (potentially divergent) objectives as aggregated into a single meta metric, particularly in context of classification involving balancing between bias / variance tradeoffs, which extend simple accuracy metrics to include alternate framings like AUC, f1 score, etc. I am wondering if such forms of aggregated metrics could be packaged into a simple Ocean packet for integration into a CQM solver?
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Hello,
Thank you for reaching out to us and for your interest in our D-Wave Systems.
At present no such functionality exists.
Please submit a Feature request to the D-Wave Ocean Tools GitHub to help promote the addition of this functionality:
New Issue · dwavesystems/dwave-ocean-sdk (github.com)
Alternatively, if you have some background in the area and are interested in contributing to the D-Wave Ocean Tools, please put together an implementation of this functionality and submit a pull request for review:
Pull requests · dwavesystems/dwave-ocean-sdk (github.com)
It is always great to have our community members get involved in the development process.
Thank you again for your interest and participation.
Please let us know if you have any questions.
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