[Machine Learning Export] - Ability to share Machine Learning data

Hello,

Is there a functionality to share the generated results from machine learning (either exporting the data or the Kibana UI) or any related posts to this topic?

Thanks,
Eric

Hi, it's not possible to export the ML graphs, but you can retrieve the results programmatically through the Machine Learning Results APIs: https://www.elastic.co/guide/en/elasticsearch/reference/6.0/ml-apis.html#ml-api-result-endpoint

The results are returned in JSON. With further processing, the results could be converted to csv or another format for sharing purposes.

Hi Jen,

Thank you for the information, I was able to extract some of the ML data. However, it seems to only be grabbing anomalies only when I am posting a GET request for records. Is this the current feature for the ML data export?

Thanks,
Eric

Hi Eric,

What data are you looking for?

Hi Rich,

I am new to this stack and was hoping to export all the data points that were used when graphing the ML job so I could generate the exact graph from the GET requests.

In addition, my GET requests return, for example, 90 records according to the count, but on the ML Kibana, I don't see as many listed in the anomalies. Do you know why that is?

Thanks,
Eric

Eric,

The first thing to know is that the index pattern that contains the information is called .ml-anomalies-* (there are index names like .ml-anomalies-shared, .ml-anomalies-jobname, etc.)

The next thing is that in those indices, there is always a key:value pair for the job_id. So, for example, job_id:orders

Lastly, in the indices, there can be 5 main kinds of results (keyed with a field called result_type)

  1. bucket
  2. record
  3. influencer
  4. model_forecast
  5. model_plot

(there are a few other types, but not worth talking about at the moment)

Each kind of result_type contains different information, but it is a summary of information gleaned from the analysis of the original raw documents that ML analyzed.

When you say "the data points that were used when graphing the ML job" - which graph are you thinking of? (perhaps also show a screenshot?)

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