linkedin / linkedin/luminol

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Dominant language
Python
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Description

Hi,

This is not really an issue but couple questions. The example code that calculates the anomaly scores e.g:

from luminol.anomaly_detector import AnomalyDetector

ts = {0: 0, 1: 0.5, 2: 1, 3: 1, 4: 1, 5: 0, 6: 0, 7: 0, 8: 0}

my_detector = AnomalyDetector(ts)
score = my_detector.get_all_scores()
for timestamp, value in score.iteritems():
print(timestamp, value)

Does it calculate the scores as they come like a real-time anomaly detection instead of looking at what the value is before? Is there a way to tune the parameters of the above code as well like the window size and chunk size? If so, how?

Thank you very much.

Contributor guide

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Research direction

Start by reviewing the AnomalyDetector example and the AnomalyDetector entry point in luminol.anomaly_detector. Determine whether the example supports real-time scoring and configurable window or chunk sizes, then document the supported behavior and usage if those answers can be established.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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