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Dos it support online mode? #5
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Thanks a lot for asking. For your quick reference, the algorithm implemented here has nothing to do with the Adam and MacKay paper. Sorry about the confusion. One major difference is that the beast algorithm seeks to decompose time series into trend and seasonality. Also, the algorithmic heuristics are different. More importantly, beast is an offline algorithm. Recently, some researchers used BEAST for online changepoint detection, and it worked. Let me know if there are any specific questions. |
thanks for your response. previously I had trouble openning your paper. But I have access now. Will read the paper first. Thanks for your help. |
Hi @zhaokg , this sounds very useful. Do you know if this has appeared in any published work yet? I would love to see how they used it. |
Hi @gwerbin , this is a paper just published today: https://www.sciencedirect.com/science/article/pii/S0924271623000424?via%3Dihub, which used the BEAST algorithm for continuous online detection. But I have to say that I did a sloppy job in implementing BEAST and it can be improved or revised to better accommodate online changepoint detection. If you see some good values of BEAST for your application, you can please share an example dataset for me to test-run and I will test the possibility of revising the algorithm for more efficient online detection. |
This is great work. I know the origional paper from Adam and MacKay talking about online changepoint. Does it support online calculation? thanks.
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