honeymoose
/
OpenSearch
mirror of https://github.com/honeymoose/OpenSearch.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

[DOCS] Adds link points to the data frame analytics supported fields (#55004) 

Co-authored-by: lcawl <lcawley@elastic.co>
This commit is contained in:
István Zoltán Szabó 2020-04-09 20:16:13 +02:00 committed by lcawl
parent 83c328f125
commit 374f633b6e
2 changed files with 39 additions and 49 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

42
docs/reference/ml/df-analytics/apis/put-dfanalytics.asciidoc
View File

@ -271,18 +271,54 @@ include::{docdir}/ml/ml-shared.asciidoc[tag=training-percent]
//Begin analyzed_fields
`analyzed_fields`::
(Optional, object)
include::{docdir}/ml/ml-shared.asciidoc[tag=analyzed-fields]
Specify `includes` and/or `excludes` patterns to select which fields will be
included in the analysis. The patterns specified in `excludes` are applied last,
therefore `excludes` takes precedence. In other words, if the same field is
specified in both `includes` and `excludes`, then the field will not be included
in the analysis.
+
--
[[dfa-supported-fields]]
The supported fields for each type of analysis are as follows:
* {oldetection-cap} requires numeric or boolean data to analyze. The algorithms
don't support missing values therefore fields that have data types other than
numeric or boolean are ignored. Documents where included fields contain missing
values, null values, or an array are also ignored. Therefore the `dest` index
may contain documents that don't have an {olscore}.
* {regression-cap} supports fields that are numeric, `boolean`, `text`,
`keyword`, and `ip`. It is also tolerant of missing values. Fields that are
supported are included in the analysis, other fields are ignored. Documents
where included fields contain an array with two or more values are also
ignored. Documents in the `dest` index that don’t contain a results field are
not included in the {reganalysis}.
* {classification-cap} supports fields that are numeric, `boolean`, `text`,
`keyword`, and `ip`. It is also tolerant of missing values. Fields that are
supported are included in the analysis, other fields are ignored. Documents
where included fields contain an array with two or more values are also ignored.
Documents in the `dest` index that don’t contain a results field are not
included in the {classanalysis}. {classanalysis-cap} can be improved by mapping
ordinal variable values to a single number. For example, in case of age ranges,
you can model the values as "0-14" = 0, "15-24" = 1, "25-34" = 2, and so on.
If `analyzed_fields` is not set, only the relevant fields will be included. For
example, all the numeric fields for {oldetection}. For more information about
field selection, see <<explain-dfanalytics>>.
--
+
.Properties of `analyzed_fields`
[%collapsible%open]
====
`excludes`:::
(Optional, array)
include::{docdir}/ml/ml-shared.asciidoc[tag=analyzed-fields-excludes]
An array of strings that defines the fields that will be excluded from the
analysis. You do not need to add fields with unsupported data types to
`excludes`, these fields are excluded from the analysis automatically.
`includes`:::
(Optional, array)
include::{docdir}/ml/ml-shared.asciidoc[tag=analyzed-fields-includes]
An array of strings that defines the fields that will be included in the
analysis.
//End analyzed_fields
====

46
docs/reference/ml/ml-shared.asciidoc
View File

@ -90,52 +90,6 @@ in memory. These limits are approximate and can be set per job. They do not
control the memory used by other processes, for example the {es} Java processes.
end::analysis-limits[]
tag::analyzed-fields[]
Specify `includes` and/or `excludes` patterns to select which fields will be
included in the analysis. The patterns specified in `excludes` are applied last,
therefore `excludes` takes precedence. In other words, if the same field is
specified in both `includes` and `excludes`, then the field will not be included
in the analysis.
+
--
The supported fields for each type of analysis are as follows:
* {oldetection-cap} requires numeric or boolean data to analyze. The algorithms
don't support missing values therefore fields that have data types other than
numeric or boolean are ignored. Documents where included fields contain missing
values, null values, or an array are also ignored. Therefore the `dest` index
may contain documents that don't have an {olscore}.
* {regression-cap} supports fields that are numeric, `boolean`, `text`,
`keyword`, and `ip`. It is also tolerant of missing values. Fields that are
supported are included in the analysis, other fields are ignored. Documents
where included fields contain an array with two or more values are also
ignored. Documents in the `dest` index that don’t contain a results field are
not included in the {reganalysis}.
* {classification-cap} supports fields that are numeric, `boolean`, `text`,
`keyword`, and `ip`. It is also tolerant of missing values. Fields that are
supported are included in the analysis, other fields are ignored. Documents
where included fields contain an array with two or more values are also ignored.
Documents in the `dest` index that don’t contain a results field are not
included in the {classanalysis}. {classanalysis-cap} can be improved by mapping
ordinal variable values to a single number. For example, in case of age ranges,
you can model the values as "0-14" = 0, "15-24" = 1, "25-34" = 2, and so on.
If `analyzed_fields` is not set, only the relevant fields will be included. For
example, all the numeric fields for {oldetection}. For more information about
field selection, see <<explain-dfanalytics>>.
--
end::analyzed-fields[]
tag::analyzed-fields-excludes[]
An array of strings that defines the fields that will be excluded from the
analysis. You do not need to add fields with unsupported data types to
`excludes`, these fields are excluded from the analysis automatically.
end::analyzed-fields-excludes[]
tag::analyzed-fields-includes[]
An array of strings that defines the fields that will be included in the
analysis.
end::analyzed-fields-includes[]
tag::assignment-explanation-anomaly-jobs[]
For open {anomaly-jobs} only, contains messages relating to the selection
of a node to run the job.