Comments (4)
Hi, @jessidirk
"w" means the size of the sliding window.
In order to know what a sliding window is, it is necessary to understand the anomaly detection method called SST.
The following papers are helpful for understanding. (Please check Figure 2)
https://ide-research.net/papers/2005_SDM_Ide.pdf
And, it is a difficult problem to decide the appropriate "w" because the appropriate value strongly depends on the target time series data. So, "w" is a hyperparameter that needs to be decided by yourself considering the periodicity of the data.
from banpei.
You're passing in data which is smaller than your window value (w
)
from banpei.
I am terribly sorry for the late confirmation.
I revised the incorrect comment.
Thank you so much!
from banpei.
Hi tsurubee! Quick question related to this issue: what is the "window value" and how do you determine what "w" is appropriate for a given dataset?
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Related Issues (10)
- ERROR: No matching distribution found for banpei HOT 1
- ERROR: Could not find a version that satisfies the requirement banpei HOT 1
- Are there any papers that can be cited? HOT 1
- demo code not working HOT 1
- detect anomalies on sequential data HOT 2
- Get the number positivity HOT 2
- test_sst.py HOT 2
- module 'banpei' has no attribute 'SST'
- Citation for banpei HOT 4
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from banpei.