This is a fascinating package that I can use in Machine Learning application. The problem here is compute complexity.
We have N votes and M candidates. Unlike normal voting where M typically is {2-10}, while N can be hundreds/thousands or millions.
In ML, I have N about a dozen votes, and M is several hundreds.
This takes a very long time to execute. Any suggestion, how I can adapt this for my "abnormal" use case?
Thanks for this amazing package. Quite useful if I can get it to run in an ML environment.
This is a fascinating package that I can use in Machine Learning application. The problem here is compute complexity.
We have N votes and M candidates. Unlike normal voting where M typically is {2-10}, while N can be hundreds/thousands or millions.
In ML, I have N about a dozen votes, and M is several hundreds.
This takes a very long time to execute. Any suggestion, how I can adapt this for my "abnormal" use case?
Thanks for this amazing package. Quite useful if I can get it to run in an ML environment.