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[7.x][DOCS] Updates ML links (#50387) (#50409)
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lcawl authored Dec 20, 2019
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2 changes: 1 addition & 1 deletion docs/reference/intro.asciidoc
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Expand Up @@ -168,7 +168,7 @@ embroidery_ needles.
==== But wait, there’s more

Want to automate the analysis of your time-series data? You can use
{stack-ov}/ml-overview.html[machine learning] features to create accurate
{ml-docs}/ml-overview.html[machine learning] features to create accurate
baselines of normal behavior in your data and identify anomalous patterns. With
machine learning, you can detect:

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Expand Up @@ -9,7 +9,7 @@ A {dfeed} resource has the following properties:
(object) If set, the {dfeed} performs aggregation searches.
Support for aggregations is limited and should only be used with
low cardinality data. For more information, see
{stack-ov}/ml-configuring-aggregation.html[Aggregating Data for Faster Performance].
{ml-docs}/ml-configuring-aggregation.html[Aggregating data for faster performance].

`chunking_config`::
(object) Specifies how data searches are split into time chunks.
Expand Down Expand Up @@ -53,7 +53,7 @@ A {dfeed} resource has the following properties:
The <<ml-detectorconfig,detector configuration objects>> in a job can contain
functions that use these script fields.
For more information, see
{stack-ov}/ml-configuring-transform.html[Transforming Data With Script Fields].
{ml-docs}/ml-configuring-transform.html[Transforming data with script fields].

`scroll_size`::
(unsigned integer) The `size` parameter that is used in {es} searches.
Expand Down Expand Up @@ -104,7 +104,7 @@ an effort to determine whether any data has subsequently been added to the index
If missing data is found, it is a good indication that the `query_delay` option
is set too low and the data is being indexed after the {dfeed} has passed that
moment in time. See
{stack-ov}/ml-delayed-data-detection.html[Working with delayed data].
{ml-docs}/ml-delayed-data-detection.html[Working with delayed data].

This check runs only on real-time {dfeeds}.

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Expand Up @@ -23,7 +23,7 @@ Deletes a filter.
[[ml-delete-filter-desc]]
==== {api-description-title}

This API deletes a {stack-ov}/ml-rules.html[filter].
This API deletes a {ml-docs}/ml-rules.html[filter].
If a {ml} job references the filter, you cannot delete the filter. You must
update or delete the job before you can delete the filter.

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Expand Up @@ -35,7 +35,7 @@ one or more forecasts before they expire.
NOTE: When you delete a job, its associated forecasts are deleted.

For more information, see
{stack-ov}/ml-overview.html#ml-forecasting[Forecasting the future].
{ml-docs}/ml-overview.html#ml-forecasting[Forecasting the future].

[[ml-delete-forecast-path-parms]]
==== {api-path-parms-title}
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Expand Up @@ -24,4 +24,4 @@ An events resource has the following properties:
in milliseconds since the epoch or ISO 8601 format.

For more information, see
{stack-ov}/ml-calendars.html[Calendars and Scheduled Events].
{ml-docs}/ml-calendars.html[Calendars and scheduled events].
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Expand Up @@ -14,4 +14,4 @@ A filter resource has the following properties:
`items`::
(array of strings) An array of strings which is the filter item list.

For more information, see {stack-ov}/ml-rules.html[Machine learning custom rules].
For more information, see {ml-docs}/ml-rules.html[Machine learning custom rules].
2 changes: 1 addition & 1 deletion docs/reference/ml/anomaly-detection/apis/forecast.asciidoc
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Expand Up @@ -23,7 +23,7 @@ Predicts the future behavior of a time series by using its historical behavior.
[[ml-forecast-desc]]
==== {api-description-title}

See {stack-ov}/ml-overview.html#ml-forecasting[Forecasting the future].
See {ml-docs}/ml-overview.html#ml-forecasting[Forecasting the future].

[NOTE]
===============================
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Expand Up @@ -29,7 +29,7 @@ You can get scheduled event information for a single calendar or for all
calendars by using `_all`.

For more information, see
{stack-ov}/ml-calendars.html[Calendars and scheduled events].
{ml-docs}/ml-calendars.html[Calendars and scheduled events].

[[ml-get-calendar-event-path-parms]]
==== {api-path-parms-title}
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Expand Up @@ -29,7 +29,7 @@ You can get information for a single calendar or for all calendars by using
`_all`.

For more information, see
{stack-ov}/ml-calendars.html[Calendars and scheduled events].
{ml-docs}/ml-calendars.html[Calendars and scheduled events].

[[ml-get-calendar-path-parms]]
==== {api-path-parms-title}
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Expand Up @@ -29,7 +29,7 @@ privileges. See <<security-privileges>> and
==== {api-description-title}

For more information about categories, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].

[[ml-get-category-path-parms]]
==== {api-path-parms-title}
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Expand Up @@ -26,7 +26,7 @@ Retrieves filters.
==== {api-description-title}

You can get a single filter or all filters. For more information, see
{stack-ov}/ml-rules.html[Machine learning custom rules].
{ml-docs}/ml-rules.html[Machine learning custom rules].

[[ml-get-filter-path-parms]]
==== {api-path-parms-title}
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Expand Up @@ -36,7 +36,7 @@ by specifying `*` as the `<job_id>`.
By default, an overall bucket has a span equal to the largest bucket span of the
specified {anomaly-jobs}. To override that behavior, use the optional
`bucket_span` parameter. To learn more about the concept of buckets, see
{stack-ov}/ml-buckets.html[Buckets].
{ml-docs}/ml-buckets.html[Buckets].

The `overall_score` is calculated by combining the scores of all the buckets
within the overall bucket span. First, the maximum `anomaly_score` per
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18 changes: 9 additions & 9 deletions docs/reference/ml/anomaly-detection/apis/jobresource.asciidoc
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Expand Up @@ -33,7 +33,7 @@ so do not set the `background_persist_interval` value too low.
`custom_settings`::
(object) Advanced configuration option. Contains custom meta data about the
job. For example, it can contain custom URL information as shown in
{stack-ov}/ml-configuring-url.html[Adding Custom URLs to Machine Learning Results].
{ml-docs}/ml-configuring-url.html[Adding custom URLs to {ml} results].

`data_description`::
(object) Describes the data format and how APIs parse timestamp fields.
Expand Down Expand Up @@ -123,7 +123,7 @@ An analysis configuration object has the following properties:
be categorized. The resulting categories must be used in a detector by setting
`by_field_name`, `over_field_name`, or `partition_field_name` to the keyword
`mlcategory`. For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing Log Messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].

`categorization_filters`::
(array of strings) If `categorization_field_name` is specified,
Expand All @@ -133,7 +133,7 @@ An analysis configuration object has the following properties:
tune the categorization by excluding sequences from consideration when
categories are defined. For example, you can exclude SQL statements that
appear in your log files. For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing Log Messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].
This property cannot be used at the same time as `categorization_analyzer`.
If you only want to define simple regular expression filters that are applied
prior to tokenization, setting this property is the easiest method.
Expand Down Expand Up @@ -256,14 +256,14 @@ NOTE: The `field_name` cannot contain double quotes or backslashes.
`function`::
(string) The analysis function that is used.
For example, `count`, `rare`, `mean`, `min`, `max`, and `sum`. For more
information, see {stack-ov}/ml-functions.html[Function Reference].
information, see {ml-docs}/ml-functions.html[Function reference].

`over_field_name`::
(string) The field used to split the data.
In particular, this property is used for analyzing the splits with respect to
the history of all splits. It is used for finding unusual values in the
population of all splits. For more information, see
{stack-ov}/ml-configuring-pop.html[Performing population analysis].
{ml-docs}/ml-configuring-pop.html[Performing population analysis].

`partition_field_name`::
(string) The field used to segment the analysis.
Expand Down Expand Up @@ -419,13 +419,13 @@ the categorization analyzer produces then you find the original document that
the categorization field value came from.

For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].

[float]
[[ml-detector-custom-rule]]
==== Detector Custom Rule

{stack-ov}/ml-rules.html[Custom rules] enable you to customize the way detectors
{ml-docs}/ml-rules.html[Custom rules] enable you to customize the way detectors
operate.

A custom rule has the following properties:
Expand Down Expand Up @@ -480,7 +480,7 @@ A condition has the following properties:

A rule is required to either have a non-empty scope or at least one condition.
For more examples see
{stack-ov}/ml-configuring-detector-custom-rules.html[Configuring Detector Custom Rules].
{ml-docs}/ml-configuring-detector-custom-rules.html[Configuring detector custom rules].

[float]
[[ml-apilimits]]
Expand All @@ -502,7 +502,7 @@ The `analysis_limits` object has the following properties:
--
NOTE: The `categorization_examples_limit` only applies to analysis that uses categorization.
For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].

--

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Expand Up @@ -23,7 +23,7 @@ Posts scheduled events in a calendar.
[[ml-post-calendar-event-desc]]
==== {api-description-title}

This API accepts a list of {stack-ov}/ml-calendars.html[scheduled events], each
This API accepts a list of {ml-docs}/ml-calendars.html[scheduled events], each
of which must have a start time, end time, and description.

[[ml-post-calendar-event-path-parms]]
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Expand Up @@ -24,7 +24,7 @@ Instantiates a calendar.
==== {api-description-title}

For more information, see
{stack-ov}/ml-calendars.html[Calendars and scheduled events].
{ml-docs}/ml-calendars.html[Calendars and scheduled events].

[[ml-put-calendar-path-parms]]
==== {api-path-parms-title}
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Expand Up @@ -23,7 +23,7 @@ Instantiates a filter.
[[ml-put-filter-desc]]
==== {api-description-title}

A {stack-ov}/ml-rules.html[filter] contains a list of strings.
A {ml-docs}/ml-rules.html[filter] contains a list of strings.
It can be used by one or more jobs. Specifically, filters are referenced in
the `custom_rules` property of <<ml-detectorconfig,detector configuration objects>>.

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Expand Up @@ -38,7 +38,7 @@ Categorization results contain the definitions of _categories_ that have been
identified. These are only applicable for jobs that are configured to analyze
unstructured log data using categorization. These results do not contain a
timestamp or any calculated scores. For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].

* <<ml-results-buckets,Buckets>>
* <<ml-results-influencers,Influencers>>
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18 changes: 9 additions & 9 deletions docs/reference/ml/ml-shared.asciidoc
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Expand Up @@ -175,7 +175,7 @@ at the same time as `categorization_filters`. The categorization analyzer
specifies how the `categorization_field` is interpreted by the categorization
process. The syntax is very similar to that used to define the `analyzer` in the
<<indices-analyze,Analyze endpoint>>. For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].
+
--
The `categorization_analyzer` field can be specified either as a string or as an
Expand Down Expand Up @@ -206,7 +206,7 @@ set this value to `0`, no examples are stored.
--
NOTE: The `categorization_examples_limit` only applies to analysis that uses
categorization. For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].

--
end::categorization-examples-limit[]
Expand All @@ -216,7 +216,7 @@ If this property is specified, the values of the specified field will be
categorized. The resulting categories must be used in a detector by setting
`by_field_name`, `over_field_name`, or `partition_field_name` to the keyword
`mlcategory`. For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages].
{ml-docs}/ml-configuring-categories.html[Categorizing log messages].
end::categorization-field-name[]

tag::categorization-filters[]
Expand All @@ -226,7 +226,7 @@ are used to filter out matching sequences from the categorization field values.
You can use this functionality to fine tune the categorization by excluding
sequences from consideration when categories are defined. For example, you can
exclude SQL statements that appear in your log files. For more information, see
{stack-ov}/ml-configuring-categories.html[Categorizing log messages]. This
{ml-docs}/ml-configuring-categories.html[Categorizing log messages]. This
property cannot be used at the same time as `categorization_analyzer`. If you
only want to define simple regular expression filters that are applied prior to
tokenization, setting this property is the easiest method. If you also want to
Expand Down Expand Up @@ -254,7 +254,7 @@ tag::custom-rules[]
An array of custom rule objects, which enable you to customize the way detectors
operate. For example, a rule may dictate to the detector conditions under which
results should be skipped. For more examples, see
{stack-ov}/ml-configuring-detector-custom-rules.html[Configuring detector custom rules].
{ml-docs}/ml-configuring-detector-custom-rules.html[Customizing detectors with custom rules].
A custom rule has the following properties:
+
--
Expand Down Expand Up @@ -318,7 +318,7 @@ end::custom-rules[]
tag::custom-settings[]
Advanced configuration option. Contains custom meta data about the job. For
example, it can contain custom URL information as shown in
{stack-ov}/ml-configuring-url.html[Adding custom URLs to {ml} results].
{ml-docs}/ml-configuring-url.html[Adding custom URLs to {ml} results].
end::custom-settings[]

tag::data-description[]
Expand Down Expand Up @@ -458,7 +458,7 @@ an effort to determine whether any data has subsequently been added to the index
If missing data is found, it is a good indication that the `query_delay` option
is set too low and the data is being indexed after the {dfeed} has passed that
moment in time. See
{stack-ov}/ml-delayed-data-detection.html[Working with delayed data].
{ml-docs}/ml-delayed-data-detection.html[Working with delayed data].

This check runs only on real-time {dfeeds}.

Expand Down Expand Up @@ -631,7 +631,7 @@ end::from[]
tag::function[]
The analysis function that is used. For example, `count`, `rare`, `mean`, `min`,
`max`, and `sum`. For more information, see
{stack-ov}/ml-functions.html[Function reference].
{ml-docs}/ml-functions.html[Function reference].
end::function[]

tag::gamma[]
Expand Down Expand Up @@ -906,7 +906,7 @@ tag::over-field-name[]
The field used to split the data. In particular, this property is used for
analyzing the splits with respect to the history of all splits. It is used for
finding unusual values in the population of all splits. For more information,
see {stack-ov}/ml-configuring-pop.html[Performing population analysis].
see {ml-docs}/ml-configuring-pop.html[Performing population analysis].
end::over-field-name[]

tag::outlier-fraction[]
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2 changes: 1 addition & 1 deletion docs/reference/modules/node.asciidoc
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Expand Up @@ -47,7 +47,7 @@ A node that has `xpack.ml.enabled` and `node.ml` set to `true`, which is the
default behavior in the {es} {default-dist}. If you want to use {ml-features},
there must be at least one {ml} node in your cluster. For more information about
{ml-features}, see
{stack-ov}/xpack-ml.html[Machine learning in the {stack}].
{ml-docs}/xpack-ml.html[Machine learning in the {stack}].
+
IMPORTANT: If you use the {oss-dist}, do not set `node.ml`. Otherwise, the node
fails to start.
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6 changes: 3 additions & 3 deletions docs/reference/redirects.asciidoc
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Expand Up @@ -611,19 +611,19 @@ See <<faster-prefix-queries>>.
=== Calendar resources

See <<ml-get-calendar>> and
{stack-ov}/ml-calendars.html[Calendars and scheduled events].
{ml-docs}/ml-calendars.html[Calendars and scheduled events].

[role="exclude",id="ml-filter-resource"]
=== Filter resources

See <<ml-get-filter>> and
{stack-ov}/ml-rules.html[Machine learning custom rules].
{ml-docs}/ml-rules.html[Machine learning custom rules].

[role="exclude",id="ml-event-resource"]
=== Scheduled event resources

See <<ml-get-calendar-event>> and
{stack-ov}/ml-calendars.html[Calendars and scheduled events].
{ml-docs}/ml-calendars.html[Calendars and scheduled events].

[role="exclude",id="index-apis"]
=== Index APIs
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2 changes: 1 addition & 1 deletion docs/reference/release-notes/highlights-7.0.0.asciidoc
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Expand Up @@ -307,7 +307,7 @@ of you running JDK 11. In order to help new users from inadvertently running
with low security, we’ve also dropped TLSv1.0 from our defaults. For those
running older versions of Java, we have default options of TLSv1.2 and
TLSv1.1. Have a look at our
https://www.elastic.co/guide/en/elastic-stack-overview/7.0/ssl-tls.html[TLS
https://www.elastic.co/guide/en/elasticsearch/reference/7.0/ssl-tls.html[TLS
setup instructions] if you need help getting started.
//end::notable-highlights[]

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2 changes: 1 addition & 1 deletion docs/reference/release-notes/highlights-7.1.0.asciidoc
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Expand Up @@ -31,7 +31,7 @@ and permissions for any user from the
https://www.elastic.co/guide/en/elasticsearch/reference/7.1/configuring-file-realm.html[file realm]
or the https://www.elastic.co/guide/en/elasticsearch/reference/7.1/configuring-native-realm.html[native realm]
. Download https://www.elastic.co/downloads/elasticsearch[Elasticsearch],
https://www.elastic.co/guide/en/elastic-stack-overview/7.1/authorization.html[configure RBAC],
https://www.elastic.co/guide/en/elasticsearch/reference/7.1/authorization.html[configure RBAC],
and run your cluster in production, knowing your private data stays private.
Note that our advanced security features, such as single sign-on and Active Directory/LDAP
authentication to field-level and document-level security, remain paid features.
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2 changes: 1 addition & 1 deletion docs/reference/release-notes/highlights-7.2.0.asciidoc
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Expand Up @@ -12,7 +12,7 @@
==== {dataframes-cap}

beta[] You can now transform your data with
{stack-ov}/ml-dataframes.html[data frames]. There is a new {kib} wizard that
{ref}/transforms.html[data frames]. There is a new {kib} wizard that
guides you through the process of creating a {dataframe-transform} to pivot and
summarize your data and store it in a new index. Alternatively, you can use
{ref}/data-frame-apis.html[{dataframe} APIs] to preview, create, and manage
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