# How to create machine learning job which compare specific times of continous days

**URL:** <https://discuss.elastic.co/t/how-to-create-machine-learning-job-which-compare-specific-times-of-continous-days/251979>\
**Category:** Kibana\
**Tags:** elastic-stack-machine-learning\
**Created:** [October 14, 2020, 2:51am UTC](https://discuss.elastic.co/t/how-to-create-machine-learning-job-which-compare-specific-times-of-continous-days/251979 "2020-10-14T02:51:46Z")\
**Posts on this page:** 5\
**Page:** 1

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**Author:** ![le\_ba\_nam](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/le_ba_nam/32/75148_2.png) [@le\_ba\_nam](https://discuss.elastic.co/u/le_ba_nam)\
**Post date:** [October 14, 2020, 2:51am UTC](https://discuss.elastic.co/t/how-to-create-machine-learning-job-which-compare-specific-times-of-continous-days/251979/1 "2020-10-14T02:51:46Z")

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I want to create job which watch the number of record exception in series of specific time of days. It means the job will compare the number exception in 6pm of each day .My team usually upcode in 2 or 3am, so by comparing the number of exception in that day with these old days, we can detect the problem.

Thanks

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**Author:** ![Tom\_Veasey](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/tom_veasey/32/47095_2.png) [@Tom\_Veasey](https://discuss.elastic.co/u/Tom_Veasey)\
**Post date:** [October 14, 2020, 4:20pm UTC](https://discuss.elastic.co/t/how-to-create-machine-learning-job-which-compare-specific-times-of-continous-days/251979/2 "2020-10-14T16:20:58Z")

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Well I would say the best thing to do is just run [high\_/low\_]count detection. We automatically model seasonality in the signal and so if you have different rates of exceptions for different times of day we _will be_ comparing the count at that time of day to the count at the same time on previous days. It does take us a little while to detect daily seasonality (but usually 3 days is sufficient).

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**Author:** ![le\_ba\_nam](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/le_ba_nam/32/75148_2.png) [@le\_ba\_nam](https://discuss.elastic.co/u/le_ba_nam)\
**Post date:** [October 16, 2020, 3:23am UTC](https://discuss.elastic.co/t/how-to-create-machine-learning-job-which-compare-specific-times-of-continous-days/251979/3 "2020-10-16T03:23:49Z")

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Did you mean 3 days in bucket span?

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**Author:** ![Tom\_Veasey](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/tom_veasey/32/47095_2.png) [@Tom\_Veasey](https://discuss.elastic.co/u/Tom_Veasey)\
**Post date:** [October 16, 2020, 8:42am UTC](https://discuss.elastic.co/t/how-to-create-machine-learning-job-which-compare-specific-times-of-continous-days/251979/4 "2020-10-16T08:42:50Z")

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What I meant was we should learn that there is daily seasonality after observing about 3 days of data, it can be a bit longer depending on the data characteristics but this is usually sufficient. This is independent of bucket length although if you use a very long bucket length, such as 1 day or more we wouldn't model daily seasonality.

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**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [November 13, 2020, 8:42am UTC](https://discuss.elastic.co/t/how-to-create-machine-learning-job-which-compare-specific-times-of-continous-days/251979/5 "2020-11-13T08:42:51Z")

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