Details
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Story
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Status: Resolved (View Workflow)
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Minor
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Resolution: Fixed
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None
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None
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ALEC20220511_Iteration_5, ALEC20220518_Iteration_6, ALEC20220608_Iteration_8
Description
We compare the performance of the DBSCAN clustering engine using "AlarmInSpaceAndTimeDistance" vs DBSCAN using Hellinger Distance. This includes cycles to test multiple combinations of said distance measures.
Eg.: DBSCAN only using Hellinger Distance with different epsilon values (tuning). Or, modify "AlarmInSpaceAndTimeDistance" formula to include Hellinger Distance.
We assume that Hellinger Distance has been implemented in ALEC and can be used/modified.
DONE CRITERIA:
- Train Neural Network to learn time distribution with key customer data.
- Compare DBSCAN+AlarmInSpaceAndTimeDistance with DBSCAN+Hellinger Distance using key customer data.
- Make an assessment of Hellinger Distance impact to ALEC existing correlation methods.
- Research write-up (confluence)
This doesn't include: * Hellinger Distance implementation in ALEC.