Comments (1)
Hey @hokiegeek2
In my case, when wanting to evaluate two levels of granularity, in fact we still only require a single analysis to be made.
An example to be clearer:
Having a dataset of
Dimension_1 | Dimension_2 | KPI
X1 | Y1 |10
...
What we want to understand is if on combination X1+Y1 there is an outlier. Therefore transforming the dataframe to only have:
Dimensions | KPI
X1,Y1 | 10
performs the exact same intent of the analysis, while passing only a single level of granularity.
Sorry for typos or formatting of the answer, hope it was helpful :)
from anomalydetection.
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from anomalydetection.