Commit Graph

14 Commits

Author SHA1 Message Date
Benjamin Trent 2279cafb4e
[ML] adding new _preview endpoint for data frame analytics (#69453)
This commit adds a new `_preview` endpoint for data frame analytics. 

This allows users to see the data on which their model will be trained. This is especially useful 
in the arrival of custom feature processors.

The API design is a similar to datafeed `_preview` and data frame analytics `_explain`.
2021-03-01 12:25:50 -05:00
Lisa Cawley 138224b398
[DOCS] Edits trained model alias API (#69491) 2021-02-24 08:17:49 -08:00
Benjamin Trent 0af38bba9e
[ML] add new delete trained model aliases API (#69195)
In addition to creating and re-assigning model aliases, users should be able to delete existing and unused model aliases.
2021-02-18 13:12:07 -05:00
Benjamin Trent 26eef892df
[ML] adds new trained model alias API to simplify trained model updates and deployments (#68922)
A `model_alias` allows trained models to be referred by a user defined moniker. 

This not only improves the readability and simplicity of numerous API calls, but it allows for simpler deployment and upgrade procedures for trained models. 

Previously, if you referenced a model ID directly within an ingest pipeline, when you have a new model that performs better than an earlier referenced model, you have to update the pipeline itself. If this model was used in numerous pipelines, ALL those pipelines would have to be updated. 

When using a `model_alias` in an ingest pipeline, only that `model_alias` needs to be updated. Then, the underlying referenced model will change in place for all ingest pipelines automatically. 

An additional benefit is that the model referenced is not changed until it is fully loaded into cache, this way throughput is not hampered by changing models.
2021-02-18 09:41:50 -05:00
Benjamin Trent 1084aaf18a
[ML] renames */inference* apis to */trained_models* (#63097)
This commit renames all `inference` CRUD APIs to `trained_models`.

This aligns with internal terminology, documentation, and use-cases.
2020-10-01 12:13:49 -04:00
Lisa Cawley 42be287b57
[DOCS] Changes level offset in data frame analytics APIs (#59919) 2020-07-20 12:11:47 -07:00
Przemysław Witek 3953de4c98
Introduce DataFrameAnalyticsConfig update API (#58302) 2020-06-29 09:26:31 +02:00
István Zoltán Szabó 67f14c3978
[DOCS] Adds PUT inference API docs (#51231)
Co-authored-by: Benjamin Trent <ben.w.trent@gmail.com>
Co-authored-by: Lisa Cawley <lcawley@elastic.co>
2020-01-31 13:12:24 +01:00
István Zoltán Szabó b683f96e23
[DOCS] Moves analysis resources to PUT DFA API docs (#50704)
Co-authored-by: Lisa Cawley <lcawley@elastic.co>
2020-01-09 13:57:11 +01:00
István Zoltán Szabó 50e26d40a2
[DOCS] Adds GET, GET stats and DELETE inference APIs (#50224)
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
2019-12-18 09:10:12 +01:00
István Zoltán Szabó 3857e3d94f
[DOCS] Moves data frame analytics job resource definitions into APIs (#50021) 2019-12-12 10:59:37 +01:00
Dimitris Athanasiou 0390ec3627
[ML] Explain data frame analytics API (#49455)
This commit replaces the _estimate_memory_usage API with
a new API, the _explain API.

The API consolidates information that is useful before
creating a data frame analytics job.

It includes:

- memory estimation
- field selection explanation

Memory estimation is moved here from what was previously
calculated in the _estimate_memory_usage API.

Field selection is a new feature that explains to the user
whether each available field was selected to be included or
not in the analysis. In the case it was not included, it also
explains the reason why.
2019-11-22 20:08:14 +02:00
Przemysław Witek 7107c221a7
Implement ml/data_frame/analytics/_estimate_memory_usage API endpoint (#45188) 2019-08-13 20:59:35 +02:00
Lisa Cawley 146be77ec3
[DOCS] Separates data frame analytics APIs (#44451)
* [DOCS] Separates data frame analytics APIs

* [DOCS] Adds links between new pages
2019-07-16 13:22:27 -07:00