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Reviews summaries of ML APIs (F-Z) (#2764)
Co-authored-by: Lisa Cawley <[email protected]> Co-authored-by: David Kyle <[email protected]>
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output/openapi/elasticsearch-openapi.json

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output/openapi/elasticsearch-serverless-openapi.json

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specification/ml/flush_job/MlFlushJobRequest.ts

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import { DateTime } from '@_types/Time'
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/**
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* Forces any buffered data to be processed by the job.
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* Force buffered data to be processed.
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* The flush jobs API is only applicable when sending data for analysis using
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* the post data API. Depending on the content of the buffer, then it might
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* additionally calculate new results. Both flush and close operations are

specification/ml/forecast/MlForecastJobRequest.ts

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import { Duration } from '@_types/Time'
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/**
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* Predicts the future behavior of a time series by using its historical
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* behavior.
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* Predict future behavior of a time series.
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*
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* Forecasts are not supported for jobs that perform population analysis; an
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* error occurs if you try to create a forecast for a job that has an
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* `over_field_name` in its configuration.
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* `over_field_name` in its configuration. Forcasts predict future behavior
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* based on historical data.
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*
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* @rest_spec_name ml.forecast
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* @availability stack since=6.1.0 stability=stable

specification/ml/get_buckets/MlGetBucketsRequest.ts

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import { DateTime } from '@_types/Time'
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/**
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* Retrieves anomaly detection job results for one or more buckets.
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* Get anomaly detection job results for buckets.
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* The API presents a chronological view of the records, grouped by bucket.
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* @rest_spec_name ml.get_buckets
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* @availability stack since=5.4.0 stability=stable

specification/ml/get_calendar_events/MlGetCalendarEventsRequest.ts

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import { DateTime } from '@_types/Time'
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/**
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* Retrieves information about the scheduled events in calendars.
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* Get info about events in calendars.
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* @rest_spec_name ml.get_calendar_events
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* @availability stack since=6.2.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/get_calendars/MlGetCalendarsRequest.ts

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import { integer } from '@_types/Numeric'
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/**
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* Retrieves configuration information for calendars.
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* Get calendar configuration info.
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* @rest_spec_name ml.get_calendars
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* @availability stack since=6.2.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/get_categories/MlGetCategoriesRequest.ts

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import { integer } from '@_types/Numeric'
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/**
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* Retrieves anomaly detection job results for one or more categories.
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* Get anomaly detection job results for categories.
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* @rest_spec_name ml.get_categories
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* @availability stack since=5.4.0 stability=stable
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* @availability serverless stability=stable visibility=private

specification/ml/get_data_frame_analytics/MlGetDataFrameAnalyticsRequest.ts

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import { integer } from '@_types/Numeric'
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/**
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* Retrieves configuration information for data frame analytics jobs.
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* Get data frame analytics job configuration info.
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* You can get information for multiple data frame analytics jobs in a single
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* API request by using a comma-separated list of data frame analytics jobs or a
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* wildcard expression.

specification/ml/get_data_frame_analytics_stats/MlGetDataFrameAnalyticsStatsRequest.ts

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import { integer } from '@_types/Numeric'
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/**
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* Retrieves usage information for data frame analytics jobs.
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* Get data frame analytics jobs usage info.
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* @rest_spec_name ml.get_data_frame_analytics_stats
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* @availability stack since=7.3.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/get_datafeed_stats/MlGetDatafeedStatsRequest.ts

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import { Ids } from '@_types/common'
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/**
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* Retrieves usage information for datafeeds.
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* Get datafeeds usage info.
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* You can get statistics for multiple datafeeds in a single API request by
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* using a comma-separated list of datafeeds or a wildcard expression. You can
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* get statistics for all datafeeds by using `_all`, by specifying `*` as the

specification/ml/get_datafeeds/MlGetDatafeedsRequest.ts

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import { Ids } from '@_types/common'
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/**
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* Retrieves configuration information for datafeeds.
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* Get datafeeds configuration info.
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* You can get information for multiple datafeeds in a single API request by
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* using a comma-separated list of datafeeds or a wildcard expression. You can
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* get information for all datafeeds by using `_all`, by specifying `*` as the

specification/ml/get_filters/MlGetFiltersRequest.ts

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import { integer } from '@_types/Numeric'
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/**
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* Retrieves filters.
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* Get filters.
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* You can get a single filter or all filters.
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* @rest_spec_name ml.get_filters
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* @availability stack since=5.5.0 stability=stable

specification/ml/get_influencers/MlGetInfluencersRequest.ts

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import { DateTime } from '@_types/Time'
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/**
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* Retrieves anomaly detection job results for one or more influencers.
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* Get anomaly detection job results for influencers.
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* Influencers are the entities that have contributed to, or are to blame for,
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* the anomalies. Influencer results are available only if an
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* `influencer_field_name` is specified in the job configuration.

specification/ml/get_job_stats/MlGetJobStatsRequest.ts

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import { Id } from '@_types/common'
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/**
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* Retrieves usage information for anomaly detection jobs.
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* Get anomaly detection jobs usage info.
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* @rest_spec_name ml.get_job_stats
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* @availability stack since=5.5.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/get_jobs/MlGetJobsRequest.ts

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import { Ids } from '@_types/common'
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/**
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* Retrieves configuration information for anomaly detection jobs.
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* Get anomaly detection jobs configuration info.
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* You can get information for multiple anomaly detection jobs in a single API
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* request by using a group name, a comma-separated list of jobs, or a wildcard
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* expression. You can get information for all anomaly detection jobs by using

specification/ml/get_memory_stats/MlGetMemoryStatsRequest.ts

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import { Duration } from '@_types/Time'
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/**
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* Get machine learning memory usage info.
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* Get information about how machine learning jobs and trained models are using memory,
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* on each node, both within the JVM heap, and natively, outside of the JVM.
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* @rest_spec_name ml.get_memory_stats

specification/ml/get_model_snapshot_upgrade_stats/MlGetModelSnapshotUpgradeStatsRequest.ts

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import { Id } from '@_types/common'
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/**
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* Retrieves usage information for anomaly detection job model snapshot upgrades.
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* Get anomaly detection job model snapshot upgrade usage info.
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* @rest_spec_name ml.get_model_snapshot_upgrade_stats
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* @availability stack since=7.16.0 stability=stable
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* @availability serverless stability=stable visibility=private

specification/ml/get_model_snapshots/MlGetModelSnapshotsRequest.ts

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import { Duration, DateTime } from '@_types/Time'
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/**
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* Retrieves information about model snapshots.
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* Get model snapshots info.
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* @rest_spec_name ml.get_model_snapshots
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* @availability stack since=5.4.0 stability=stable
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* @availability serverless stability=stable visibility=private

specification/ml/get_overall_buckets/MlGetOverallBucketsRequest.ts

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import { Duration, DateTime } from '@_types/Time'
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/**
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* Retrieves overall bucket results that summarize the bucket results of
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* Get overall bucket results.
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*
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* Retrievs overall bucket results that summarize the bucket results of
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* multiple anomaly detection jobs.
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*
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* The `overall_score` is calculated by combining the scores of all the

specification/ml/get_records/MlGetAnomalyRecordsRequest.ts

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/**
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* Retrieves anomaly records for an anomaly detection job.
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* Get anomaly records for an anomaly detection job.
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* Records contain the detailed analytical results. They describe the anomalous
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* activity that has been identified in the input data based on the detector
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* configuration.

specification/ml/get_trained_models/MlGetTrainedModelRequest.ts

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import { Include } from '@ml/_types/Include'
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/**
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* Retrieves configuration information for a trained model.
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* Get trained model configuration info.
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* @rest_spec_name ml.get_trained_models
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* @availability stack since=7.10.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/get_trained_models_stats/MlGetTrainedModelStatsRequest.ts

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/**
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* Retrieves usage information for trained models. You can get usage information for multiple trained
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* Get trained models usage info.
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* You can get usage information for multiple trained
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* models in a single API request by using a comma-separated list of model IDs or a wildcard expression.
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* @rest_spec_name ml.get_trained_models_stats
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* @availability stack since=7.10.0 stability=stable

specification/ml/infer_trained_model/MlInferTrainedModelRequest.ts

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/**
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* Evaluates a trained model.
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* Evaluate a trained model.
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* @rest_spec_name ml.infer_trained_model
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* @availability stack since=8.3.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/info/MlInfoRequest.ts

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/**
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* Return ML defaults and limits.
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* Returns defaults and limits used by machine learning.
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* This endpoint is designed to be used by a user interface that needs to fully
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* understand machine learning configurations where some options are not

specification/ml/open_job/MlOpenJobRequest.ts

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/**
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* Open anomaly detection jobs.
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* An anomaly detection job must be opened in order for it to be ready to
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* receive and analyze data. It can be opened and closed multiple times
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* throughout its lifecycle.
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* An anomaly detection job must be opened to be ready to receive and analyze
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* data. It can be opened and closed multiple times throughout its lifecycle.
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* When you open a new job, it starts with an empty model.
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* When you open an existing job, the most recent model state is automatically
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* loaded. The job is ready to resume its analysis from where it left off, once

specification/ml/post_calendar_events/MlPostCalendarEventsRequest.ts

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import { CalendarEvent } from '../_types/CalendarEvent'
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/**
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* Adds scheduled events to a calendar.
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* Add scheduled events to the calendar.
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* @rest_spec_name ml.post_calendar_events
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* @availability stack since=6.2.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/post_data/MlPostJobDataRequest.ts

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/**
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* Sends data to an anomaly detection job for analysis.
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* Send data to an anomaly detection job for analysis.
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*
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* IMPORTANT: For each job, data can be accepted from only a single connection at a time.
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* It is not currently possible to post data to multiple jobs using wildcards or a comma-separated list.

specification/ml/preview_data_frame_analytics/MlPreviewDataFrameAnalyticsRequest.ts

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/**
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* Preview features used by data frame analytics.
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* Previews the extracted features used by a data frame analytics config.
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* @rest_spec_name ml.preview_data_frame_analytics
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* @availability stack since=7.13.0 stability=stable

specification/ml/preview_datafeed/MlPreviewDatafeedRequest.ts

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/**
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* Previews a datafeed.
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* Preview a datafeed.
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* This API returns the first "page" of search results from a datafeed.
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* You can preview an existing datafeed or provide configuration details for a datafeed
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* and anomaly detection job in the API. The preview shows the structure of the data

specification/ml/put_calendar/MlPutCalendarRequest.ts

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/**
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* Creates a calendar.
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* Create a calendar.
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* @rest_spec_name ml.put_calendar
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* @availability stack since=6.2.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/put_calendar_job/MlPutCalendarJobRequest.ts

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/**
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* Adds an anomaly detection job to a calendar.
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* Add anomaly detection job to calendar.
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* @rest_spec_name ml.put_calendar_job
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* @availability stack since=6.2.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts

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/**
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* Instantiates a data frame analytics job.
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* Create a data frame analytics job.
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* This API creates a data frame analytics job that performs an analysis on the
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* source indices and stores the outcome in a destination index.
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* @rest_spec_name ml.put_data_frame_analytics

specification/ml/put_datafeed/MlPutDatafeedRequest.ts

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* Instantiates a datafeed.
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* Create a datafeed.
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* Datafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.
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* The datafeed contains a query that runs at a defined interval (`frequency`).

specification/ml/put_filter/MlPutFilterRequest.ts

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/**
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* Instantiates a filter.
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* Create a filter.
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* A filter contains a list of strings. It can be used by one or more anomaly detection jobs.
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* Specifically, filters are referenced in the `custom_rules` property of detector configuration objects.
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* @rest_spec_name ml.put_filter

specification/ml/put_trained_model/MlPutTrainedModelRequest.ts

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* Enables you to supply a trained model that is not created by data frame analytics.
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* Create a trained model.
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* Enable you to supply a trained model that is not created by data frame analytics.
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* @rest_spec_name ml.put_trained_model
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specification/ml/put_trained_model_alias/MlPutTrainedModelAliasRequest.ts

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* Creates or updates a trained model alias. A trained model alias is a logical
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* name used to reference a single trained model.
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* Create or update a trained model alias.
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* A trained model alias is a logical name used to reference a single trained
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* model.
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* You can use aliases instead of trained model identifiers to make it easier to
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* aggregations and processors.

specification/ml/put_trained_model_definition_part/MlPutTrainedModelDefinitionPartRequest.ts

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* Create part of a trained model definition.
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* @rest_spec_name ml.put_trained_model_definition_part
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* @availability stack since=8.0.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/put_trained_model_vocabulary/MlPutTrainedModelVocabularyRequest.ts

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/**
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* Creates a trained model vocabulary.
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* Create a trained model vocabulary.
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* This API is supported only for natural language processing (NLP) models.
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* The vocabulary is stored in the index as described in `inference_config.*.vocabulary` of the trained model definition.
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* @rest_spec_name ml.put_trained_model_vocabulary

specification/ml/reset_job/MlResetJobRequest.ts

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/**
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* Resets an anomaly detection job.
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* Reset an anomaly detection job.
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* All model state and results are deleted. The job is ready to start over as if
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* it had just been created.
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* It is not currently possible to reset multiple jobs using wildcards or a

specification/ml/revert_model_snapshot/MlRevertModelSnapshotRequest.ts

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/**
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* Reverts to a specific snapshot.
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* Revert to a snapshot.
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* The machine learning features react quickly to anomalous input, learning new
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* behaviors in data. Highly anomalous input increases the variance in the
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* models whilst the system learns whether this is a new step-change in behavior

specification/ml/set_upgrade_mode/MlSetUpgradeModeRequest.ts

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* Set upgrade_mode for ML indices.
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* Sets a cluster wide upgrade_mode setting that prepares machine learning
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* indices for an upgrade.
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* When upgrading your cluster, in some circumstances you must restart your

specification/ml/start_data_frame_analytics/MlStartDataFrameAnalyticsRequest.ts

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* Starts a data frame analytics job.
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* Start a data frame analytics job.
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* A data frame analytics job can be started and stopped multiple times
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* throughout its lifecycle.
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* If the destination index does not exist, it is created automatically the

specification/ml/start_datafeed/MlStartDatafeedRequest.ts

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@@ -22,7 +22,7 @@ import { Id } from '@_types/common'
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import { Duration, DateTime } from '@_types/Time'
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/**
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* Starts one or more datafeeds.
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* Start datafeeds.
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*
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* A datafeed must be started in order to retrieve data from Elasticsearch. A datafeed can be started and stopped
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* multiple times throughout its lifecycle.

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