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-<!--
-title: "double exponential smoothing"
-sidebar_label: "double exponential smoothing"
-custom_edit_url: https://github.com/netdata/netdata/edit/master/web/api/queries/des/README.md
-learn_status: "Published"
-learn_topic_type: "References"
-learn_rel_path: "Developers/Web/Api/Queries"
--->
-
-# double exponential smoothing
-
-Exponential smoothing is one of many window functions commonly applied to smooth data in signal
-processing, acting as low-pass filters to remove high frequency noise.
-
-Simple exponential smoothing does not do well when there is a trend in the data.
-In such situations, several methods were devised under the name "double exponential smoothing"
-or "second-order exponential smoothing.", which is the recursive application of an exponential
-filter twice, thus being termed "double exponential smoothing".
-
-In simple terms, this is like an average value, but more recent values are given more weight
-and the trend of the values influences significantly the result.
-
-> **IMPORTANT**
->
-> It is common for `des` to provide "average" values that far beyond the minimum or the maximum
-> values found in the time-series.
-> `des` estimates these values because of it takes into account the trend.
-
-This module implements the "Holt-Winters double exponential smoothing".
-
-Netdata automatically adjusts the weight (`alpha`) and the trend (`beta`) based on the number
-of values processed, using the formula:
-
-```
-window = max(number of values, 15)
-alpha = 2 / (window + 1)
-beta = 2 / (window + 1)
-```
-
-You can change the fixed value `15` by setting in `netdata.conf`:
-
-```
-[web]
- des max window = 15
-```
-
-## how to use
-
-Use it in alerts like this:
-
-```
- alarm: my_alert
- on: my_chart
-lookup: des -1m unaligned of my_dimension
- warn: $this > 1000
-```
-
-`des` does not change the units. For example, if the chart units is `requests/sec`, the result
-will be again expressed in the same units.
-
-It can also be used in APIs and badges as `&group=des` in the URL.
-
-## Examples
-
-Examining last 1 minute `successful` web server responses:
-
-- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=min&after=-60&label=min)
-- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=average&after=-60&label=average&value_color=yellow)
-- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=ses&after=-60&label=single+exponential+smoothing&value_color=yellow)
-- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=des&after=-60&label=double+exponential+smoothing&value_color=orange)
-- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=max&after=-60&label=max)
-
-## References
-
-- <https://en.wikipedia.org/wiki/Exponential_smoothing>.
-
-