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Acronym SDD to be added into the terminology part.
3.1. Collection: The duration of retention is relatively trivial in the collection phase due to the resource limitation. it's much more important in the long-term storage after the aggregation step. Instead, data granularity and sampling rate, aggregation time bucket during the collection may be more worth mentioning.
3.3.4. Machine Learning approaches:
(Just input, this part might be removed for the first version ACK)
+ discover what people don't see
- requires data quality (ground truth) and data amount
- hard to adjust, no much control
- sometimes can be resource intensive (eg. multiple models per one @vpn)
The text was updated successfully, but these errors were encountered:
I'm not sure duration of retention is that trivial :)
I would suggest we go into aggregation time bucketing as well as sampling rate in a next revision?
Service disruption detection VS Anomaly detection
Acronym SDD to be added into the terminology part.
3.1. Collection: The duration of retention is relatively trivial in the collection phase due to the resource limitation. it's much more important in the long-term storage after the aggregation step. Instead, data granularity and sampling rate, aggregation time bucket during the collection may be more worth mentioning.
3.3.4. Machine Learning approaches:
(Just input, this part might be removed for the first version ACK)
+ discover what people don't see
- requires data quality (ground truth) and data amount
- hard to adjust, no much control
- sometimes can be resource intensive (eg. multiple models per one @vpn)
The text was updated successfully, but these errors were encountered: