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Diffstat (limited to 'docs/cloud/insights/anomaly-advisor.md')
-rw-r--r-- | docs/cloud/insights/anomaly-advisor.md | 2 |
1 files changed, 0 insertions, 2 deletions
diff --git a/docs/cloud/insights/anomaly-advisor.md b/docs/cloud/insights/anomaly-advisor.md index 0e99522c4b..adce593a4d 100644 --- a/docs/cloud/insights/anomaly-advisor.md +++ b/docs/cloud/insights/anomaly-advisor.md @@ -32,8 +32,6 @@ To enable ML on your Netdata Agent, you need to edit the `[ml]` section in your At a minimum you just need to set `enabled = yes` to enable ML with default params. More details about configuration can be found in the [Netdata Agent ML docs](https://learn.netdata.cloud/docs/agent/ml#configuration). -**Note**: Follow [this guide](https://github.com/netdata/netdata/blob/master/docs/guides/step-by-step/step-04.md) if you are unfamiliar with making configuration changes in Netdata. - When you have finished your configuration, restart Netdata with a command like `sudo systemctl restart netdata` for the config changes to take effect. You can find more info on restarting Netdata [here](https://github.com/netdata/netdata/blob/master/docs/configure/start-stop-restart.md). After a brief delay, you should see the number of `trained` dimensions start to increase on the "dimensions" chart of the "Anomaly Detection" menu on the Overview page. By default the `minimum num samples to train = 3600` parameter means at least 1 hour of data is required to train initial models, but you could set this to `900` if you want to train initial models quicker but on less data. Over time, they will retrain on up to `maximum num samples to train = 14400` (4 hours by default), but you could increase this is you wanted to train on more data. |