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This repository contains the time series segmentation benchmark (TSSB).

License: BSD 3-Clause "New" or "Revised" License

Jupyter Notebook 97.95% Python 2.05%
change-point change-point-detection machine-learning python research science segmentation time-series time-series-analysis unsupervised-learning data-mining data-science time-series-segmentation time-series-data-mining

time-series-segmentation-benchmark's Issues

multi-dimension data

Hi,

Thank you for providing this package. I successfully installed it. However, it seems can not deal with multi-channel inputs. When I feed a 5-dimensional time series, I get an error.

Thank you for your reply in advance.

Images

Hello, i I succeeded to run your code. But does your code generated the visualization?

Where does the ground truth changepoint indexes come from?

Hello!

In this library I noticed that there are only a couple of multivariate data sets available.

I understand that the source of all this data is UEA & UCR time series classification. Since they've expanded the multivariate section to ~30 data sets I was hoping to also find the ground truth changepoints associated to those data sets.

In this library I see that the change point ground truth comes from this desc.txt file.

Would you be so kind as to point me in the direction of how I can derive these ground truth segments for more data sets found on UEA & UCR time series classification?

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