Hi,
When configuring Machine Learning jobs in ES, you can customise your detectors by using custom_rules.
I'm wondering about the actual meaning of the applies_to
value diff_from_typical
. My main question is if diff_from_typical
considers difference in an absolute way or not. I know then you can use lt
or gt
operators (among others) but let's image the following situation:
I have a custom rule for two jobs. The rule is the same but the cases scenarios are different. Let's say that the custom rule is:
"custom_rules": [{
"actions": ["skip_model_update"],
"conditions": [
{
"applies_to": "diff_from_typical",
"operator": "gt",
"value": 2000
}
]
}]
Case scenario A:
- Typical value: 5000
- Actual value: 2000
- diff_from_typical: 5000 - 2000 = 3000
Case scenario B:
- Typical value: 5000
- Actual value: 8000
- diff_from_typical: 5000 - 8000 = -3000
Will the aforementioned custom rule apply in both cases? I mean, using the absolute difference from typical? Or will it only work in the first case (case A)?
I assume that if it only works for the first case, I should write the "inverse" custom rule to manage both cases.
Thanks in advance!