timeseries
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KMeans question
Hi, Thanks for the awesome library!
So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).
I conceptually
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Implement __sub__
Currently one cannot just do -SomeLoss(). Of course it could be hacked by doing (-1) * SomeLoss(). We want to implement the first syntax via __sub__.
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it's becoming more time-consuming and error-prone to manually re-test all the demos following internal refactorings and API adjustments.
now that the API is fleshed out a bit, it's possible to test a large amount of code (non-granularly) without having to simulate all interactions via Puppeteer or similar.
a lot of code can already be regression-tested by simply running all the demos and val