Adds a new parameter for classification that enables choosing whether to assign labels to
maximise accuracy or to maximise the minimum class recall.
Fixes#52427.
This changes the `top_metrics` aggregation to return metrics in their
original type. Since it only supports numerics, that means that dates,
longs, and doubles will come back as stored, with their appropriate
formatter applied.
Adds a new `default_field_map` field to trained model config objects.
This allows the model creator to supply field map if it knows that there should be some map for inference to work directly against the training data.
The use case internally is having analytics jobs supply a field mapping for multi-field fields. This allows us to use the model "out of the box" on data where we trained on `foo.keyword` but the `_source` only references `foo`.
Currently the AbstractBulkByScrollRequest accepts slice values of 0 via its
`setSlices` method, denoting the "auto" slicing behaviour that is usable by
settting the "slices=auto" parameter on rest requests. When using the High Level
Rest Client, however, we send the 0 value as an integer, which is then rejected
as invalid by `AbstractBulkByScrollRequest#parseSlices`. Instead of making
parsing of the rest request more lenient, this PR opts for changing the
RequestConverter logic in the client to translate 0 values to "auto" on the rest
requests.
Closes#53044
Adds reporting of memory usage for data frame analytics jobs.
This commit introduces a new index pattern `.ml-stats-*` whose
first concrete index will be `.ml-stats-000001`. This index serves
to store instrumentation information for those jobs.
Backport of #52778 and #52958
* [ML][Inference] Add support for multi-value leaves to the tree model (#52531)
This adds support for multi-value leaves. This is a prerequisite for multi-class boosted tree classification.
This adds a new configurable field called `indices_options`. This allows users to create or update the indices_options used when a datafeed reads from an index.
This is necessary for the following use cases:
- Reading from frozen indices
- Allowing certain indices in multiple index patterns to not exist yet
These index options are available on datafeed creation and update. Users may specify them as URL parameters or within the configuration object.
closes https://github.com/elastic/elasticsearch/issues/48056
The `top_metrics` agg is kind of like `top_hits` but it only works on
doc values so it *should* be faster.
At this point it is fairly limited in that it only supports a single,
numeric sort and a single, numeric metric. And it only fetches the "very
topest" document worth of metric. We plan to support returning a
configurable number of top metrics, requesting more than one metric and
more than one sort. And, eventually, non-numeric sorts and metrics. The
trick is doing those things fairly efficiently.
Co-Authored by: Zachary Tong <zach@elastic.co>
This adds a builder and parsed results for the `string_stats`
aggregation directly to the high level rest client. Without this the
HLRC can't access the `string_stats` API without the elastic licensed
`analytics` module.
While I'm in there this adds a few of our usual unit tests and
modernizes the parsing.
This change adds support for the following new model_size_stats
fields:
- categorized_doc_count
- total_category_count
- frequent_category_count
- rare_category_count
- dead_category_count
- categorization_status
Backport of #51879
in preparation for feature importance and split information gain, adding `number_samples` field to `TreeNode` definition.
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
The main purpose of this commit is to add a single autoscaling REST
endpoint skeleton, for the purpose of starting to build out the build
and testing infrastructure that will surround it. For example, rather
than commiting a fully-functioning autoscaling API, we introduce here
the skeleton so that we can start wiring up the build and testing
infrastructure, establish security roles/permissions, an so on. This
way, in a forthcoming PR that introduces actual functionality, that PR
will be smaller and have less distractions around that sort of
infrastructure.
* [ML][Inference] Fix weighted mode definition (#51648)
Weighted mode inaccurately assumed that the "max value" of the input values would be the maximum class value. This does not make sense.
Weighted Mode should know how many classes there are. Hence the new parameter `num_classes`. This indicates what the maximum class value to be expected.
This commit creates a new index privilege named `maintenance`.
The privilege grants the following actions: `refresh`, `flush` (also synced-`flush`),
and `force-merge`. Previously the actions were only under the `manage` privilege
which in some situations was too permissive.
Co-authored-by: Amir H Movahed <arhd83@gmail.com>
* [ML][Inference] add tags url param to GET (#51330)
Adds a new URL parameter, `tags` to the GET _ml/inference/<model_id> endpoint.
This parameter allows the list of models to be further reduced to those who contain all the provided tags.
* [ML][Inference] Adding classification_weights to ensemble models
classification_weights are a way to allow models to
prefer specific classification results over others
this might be advantageous if classification value
probabilities are a known quantity and can improve
model error rates.
Adds a new parameter to regression and classification that enables computation
of importance for the top most important features. The computation of the importance
is based on SHAP (SHapley Additive exPlanations) method.
Backport of #50914
* [ML][Inference] PUT API (#50852)
This adds the `PUT` API for creating trained models that support our format.
This includes
* HLRC change for the API
* API creation
* Validations of model format and call
* fixing backport
Since 6.0, the 'template' field has been deprecated in put template requests in
favour of index_patterns. Previously, the PutIndexTemplateRequest would accept
the 'template' field in its 'source' methods and silently convert it to
'index_patterns'. This meant that users specifying 'template' in the source
would not receive a deprecation warning from the server.
This PR makes a small change to no longer silently convert 'template' to
'index_patterns', which ensures that users receive a deprecation warning.
Follow-up to #49460.
Replaces the "funny"
`Function<String, ConstructingObjectParser<T, Void>>` with a much
simpler `ConstructingObjectParser<T, String>`. This makes pretty much
all of our object parsers static.
This adds the necessary named XContent classes to the HLRC for the lang ident model. This is so the HLRC can call `GET _ml/inference/lang_ident_model_1?include_definition=true` without XContent parsing errors.
The constructors are package private as since this classes are used exclusively within the pre-packaged model (and require the specific weights, etc. to be of any use).
We have about 800 `ObjectParsers` in Elasticsearch, about 700 of which
are final. This is *probably* the right way to declare them because in
practice we never mutate them after they are built. And we certainly
don't change the static reference. Anyway, this adds `final` to these
parsers.
I found the non-final parsers with this:
```
diff \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*PARSER\s*=' {} \+ | sort) \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*final.*PARSER\s*=' {} \+ | sort) \
2>&1 | grep '^<'
```
Adds a `force` parameter to the delete data frame analytics
request. When `force` is `true`, the action force-stops the
jobs and then proceeds to the deletion. This can be used in
order to delete a non-stopped job with a single request.
Closes#48124
Backport of #50553
We have about 800 `ObjectParsers` in Elasticsearch, about 700 of which
are final. This is *probably* the right way to declare them because in
practice we never mutate them after they are built. And we certainly
don't change the static reference. Anyway, this adds `final` to a bunch
of these parsers, mostly the ones in xpack and their "paired" parsers in
the high level rest client. I picked these just to have somewhere to
break the up the change so it wouldn't be huge.
I found the non-final parsers with this:
```
diff \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*PARSER\s*=' {} \+ | sort) \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*final.*PARSER\s*=' {} \+ | sort) \
2>&1 | grep '^<'
```
The additional change to the original PR (#49657), is that `org.elasticsearch.client.cluster.RemoteConnectionInfo` now parses the initial_connect_timeout field as a string instead of a TimeValue instance.
The reason that this is needed is because that the initial_connect_timeout field in the remote connection api is serialized for human consumption, but not for parsing purposes.
Therefore the HLRC can't parse it correctly (which caused test failures in CI, but not in the PR CI
:( ). The way this field is serialized needs to be changed in the remote connection api, but that is a breaking change. We should wait making this change until rest api versioning is introduced.
Co-Authored-By: j-bean <anton.shuvaev91@gmail.com>
Co-authored-by: j-bean <anton.shuvaev91@gmail.com>
This adds a new `randomize_seed` for regression and classification.
When not explicitly set, the seed is randomly generated. One can
reuse the seed in a similar job in order to ensure the same docs
are picked for training.
Backport of #49990
This adds a `_source` setting under the `source` setting of a data
frame analytics config. The new `_source` is reusing the structure
of a `FetchSourceContext` like `analyzed_fields` does. Specifying
includes and excludes for source allows selecting which fields
will get reindexed and will be available in the destination index.
Closes#49531
Backport of #49690
