# Kibana ML anomalies detection and regression **URL:** \ **Category:** Kibana\ **Tags:** elastic-stack-machine-learning\ **Created:** [July 20, 2020, 1:17pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894 "2020-07-20T13:17:58Z")\ **Posts on this page:** 14\ **Page:** 1
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [July 20, 2020, 1:17pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/1 "2020-07-20T13:17:58Z")
Hi, I have trend data and i want to identify customers whose turnover climb or fall . Witch Kibana ML model can i do to identify them? Anomalies detection or regression ? I also want to know how to interpret the results of anomalies detection based on poplulation metric and how to interpret the result of a regression? For regression per example, i have done an analysis witch predict the turnover. But i dont know what to do with the result? How can i interpret that( i have training r2 =0,7 and testing r2=0,4). when can i say my model is good? How the regression analysis in kibana works? I have used a training percent of 90. This normaly means that 90% of data is used for training and 10% for testing. is the 10% a part of my data or is this unseen data that kibana will generate? Thanks for answers. Cordialy ---
**Author:** ![richcollier](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/richcollier/32/115035_2.png) [@richcollier](https://discuss.elastic.co/u/richcollier)\ **Post date:** [July 20, 2020, 4:32pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/2 "2020-07-20T16:32:39Z")
If you have a time-series based trend-line of the rates of customer turnovers, you can certainly use anomaly detection to assess if the current rate is higher/lower than typical. If you are trying to assess/predict whether or not a specific customer is likely to turnover or not (based upon the values of other fields that could be indicative), then a classification analytics job would be the right approach. See a good example of that here: [https://www.elastic.co/webinars/introduction-to-supervised-machine-learning-in-elastic](https://www.elastic.co/webinars/introduction-to-supervised-machine-learning-in-elastic) ---
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [July 31, 2020, 12:08pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/3 "2020-07-31T12:08:43Z")
Thanks Richcollier.. So can you explain me please how the typical value is calculated?? I have some values that i don't understand. ---
**Author:** ![richcollier](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/richcollier/32/115035_2.png) [@richcollier](https://discuss.elastic.co/u/richcollier)\ **Post date:** [July 31, 2020, 12:51pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/4 "2020-07-31T12:51:26Z")
The `actual` value is from the raw data itself (the data ML is analyzing). The `typical` value is the highest probable value from the internal statistical model that ML has constructed for that data set. Perhaps a [basic introductory video](https://www.youtube.com/watch?v=n6xW6YWYgs0) on ML's anomaly detection would be helpful. ---
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [July 31, 2020, 12:55pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/5 "2020-07-31T12:55:51Z")
Okay thank you.. But what are exactly the statistical models that are used to calculate typical values? ---
**Author:** ![richcollier](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/richcollier/32/115035_2.png) [@richcollier](https://discuss.elastic.co/u/richcollier)\ **Post date:** [July 31, 2020, 1:10pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/6 "2020-07-31T13:10:03Z")
We designed them. You can get a sense of the foundation by looking at this whitepaper: [http://www.ijmlc.org/papers/398-LC018.pdf](http://www.ijmlc.org/papers/398-LC018.pdf) Or probably easier is to watch this: [https://www.elastic.co/elasticon/conf/2017/sf/machine-learning-and-statistical-methods-for-time-series-analysis](https://www.elastic.co/elasticon/conf/2017/sf/machine-learning-and-statistical-methods-for-time-series-analysis) ---
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [August 3, 2020, 8:36am UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/7 "2020-08-03T08:36:59Z")
Hi Richcollier, I have another question..my typical value are like this.see screenshot. I think this is not normal..what do you think?? ![Capture_typical](https://us1.discourse-cdn.com/elastic/original/3X/c/e/ced7925d498e7e673d0aec7b00068e5233af0a3f.png) ---
**Author:** ![richcollier](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/richcollier/32/115035_2.png) [@richcollier](https://discuss.elastic.co/u/richcollier)\ **Post date:** [August 3, 2020, 1:01pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/8 "2020-08-03T13:01:41Z")
I'm not sure I understand why you think those values look incorrect. Can you provide more context and/or the reason why you think that? ---
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [August 4, 2020, 8:45am UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/9 "2020-08-04T08:45:59Z")
I think that because typical values are supposed to be the "highest probable values (p-value)" so it should be a value between 0 and 1. is it correct?? but in my screenshot I have values ​​greater than 1. on the other hand the p value is not smaller than 0.05 does that mean that the result is not significant? Cordialy, ---
**Author:** ![richcollier](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/richcollier/32/115035_2.png) [@richcollier](https://discuss.elastic.co/u/richcollier)\ **Post date:** [August 4, 2020, 11:51am UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/10 "2020-08-04T11:51:02Z")
The typical value is the highest probable value of the measurement, not the highest probability. As an analogy, the highest probable value of a two dice being rolled is "7" ---
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [August 4, 2020, 12:06pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/11 "2020-08-04T12:06:04Z")
Okay I understand better.. But i still dont understand my result. I have got this result after the analysis ![Capture_typical_actual](https://us1.discourse-cdn.com/elastic/original/3X/5/5/55f6f7a5841ee2fffa3848a0491453a911d51b34.png) ---
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [August 4, 2020, 12:07pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/12 "2020-08-04T12:07:39Z")
As you see there is a big gap beetween the actual and the typycal values.. ---
**Author:** ![ahadi](https://avatars.discourse-cdn.com/v4/letter/a/ee7513/32.png) [@ahadi](https://discuss.elastic.co/u/ahadi)\ **Post date:** [August 4, 2020, 12:15pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/13 "2020-08-04T12:15:59Z")
ignore my last posts @richcollier i understood. Thank you very much ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [September 1, 2020, 12:16pm UTC](https://discuss.elastic.co/t/kibana-ml-anomalies-detection-and-regression/241894/14 "2020-09-01T12:16:07Z")
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