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License: MIT License
Anomaly detection library based on singular spectrum transformation(sst)
License: MIT License
Hello
Nothing happens when I run the "sst_detect.py" code under the "demo" folder.
I am using python 3.7 on Windows 10.
regards,
banpei/banpei/sst.py 50行目
Input data is too small.
がよいかと思われます。
Hi
i'm working on anomaly detection on energy consumption so i have a semi-sequential data. i tested the sst method and i don't think it works form me because it just detect a changing point, i tried to test the Hotelling method but i didn't understand how it works, can someone help me please.
I am trying to do pipenv install banpei
in my virtual env, it is throwing the following error:
Installing banpei…
Error: An error occurred while installing banpei!
Error text:
ERROR: Could not find a version that satisfies the requirement banpei (from -r /tmp/pipenv-00uw2ca1-requirements/pipenv-x3l4m4in-requirement.txt (line 1)) (from versions: none)
ERROR: No matching distribution found for banpei (from -r /tmp/pipenv-00uw2ca1-requirements/pipenv-x3l4m4in-requirement.txt (line 1))
Hello,
I am using banpei for change point detection in my thesis. I would like to cite this work but could not find any citations. It would be great to have Bibtex entry for citation.
Thank You
Hello,
I have tried to run the tests/test_sst.py.
I got following output:
``test_sst.py -v
test_detect_by_lanczos (main.TestSST) ... ok
test_detect_by_svd (main.TestSST) ... ok
test_stream_detect (main.TestSST) ... ok
Ran 3 tests in 0.019s
OK
``
How do I get the change point score as an output?
Thanks
I want to use your method in the paper, are there any paper that can be cited, tks very much!
I have a rule that throws numbers between -50 and 50 randomly, is there any way to predict the sign (positive or negative) of the next release with at least 90% accuracy based on a historical record?
Following the Usage tutorial got the following error:
AttributeError Traceback (most recent call last)
<ipython-input-6-99f3ee034564> in <module>
----> 1 model = banpei.SST(w=20)
2 results = model.detect(data)
AttributeError: module 'banpei' has no attribute 'SST'
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