[DOCS] Adds data frame analytics API and evaluate API resource documentation

docs/reference/ml/apis/dfanalyticsresources.asciidoc

@@ -0,0 +1,94 @@
+[role="xpack"]
+[testenv="platinum"]
+[[ml-dfanalytics-resources]]
+=== {dfanalytics-cap} resources
+
+A {dfanalytics} configuration object has the following properties:
+
+`analysis`::
+  (object) The type of analysis that is performed on the `source`. For example: 
+  `outlier_detection`. For more information, see <<dfanalytics-types>>.
+
+`analyzed_fields`::
+  (object) You can specify both `includes` and/or `excludes` patterns. If 
+  `analyzed_fields` is not set, only the relevant fileds will be included. For 
+  example all the numeric fields for {oldetection}.
+
+`dest`::
+  (object) The destination configuration of the analysis. For more information, 
+  see <<dfanalytics-dest-resources>>.
+
+`id`::
+  (string) The unique identifier for the {dfanalytics-job}. This identifier can 
+  contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and 
+  underscores. It must start and end with alphanumeric characters. This property 
+  is informational; you cannot change the identifier for existing jobs.
+
+`model_memory_limit`::
+  (string) The approximate maximum amount of memory resources that are 
+  required for analytical processing. The default value for {dfanalytics-jobs} 
+  is `1gb`. If your `elasticsearch.yml` file contains an 
+  `xpack.ml.max_model_memory_limit` setting, an error occurs when you try to 
+  create {dfanalytics-jobs} that have `model_memory_limit` values greater than 
+  that setting. For more information, see <<ml-settings>>.
+
+`source`::
+  (object) The source configuration, consisting of `index` and optionally a 
+  `query`. For more information, see <<dfanalytics-source-resources>>.
+
+[float]
+[[dfanalytics-types]]
+==== Analysis types
+
+[float]
+[[oldetection-resources]]
+===== {oldetection-cap} configuration objects 
+
+An {oldetection} configuration object has the following properties:
+
+`n_neighbors` (Optional)::
+  (integer) Defines the value for how many nearest neighbors each method of 
+  {oldetection} will use to calculate its {olscore}. When the value is 
+  not set, the system will dynamically detect an appropriate value.
+
+`method` (Optional)::
+  (string) Sets the method that {oldetection} uses. If the method is not set 
+  {oldetection} uses an ensemble of different methods and normalises and 
+  combines their individual {olscores} to obtain the overall {olscore}. 
+  Available methods are `lof`, `ldof`, `distance_kth_nn`, `distance_knn`.
+
+`feature_influence_threshold` (Optional):: 
+  (double) The minimum {olscore} that a document needs to have in order to 
+  calculate its {fiscore}. 
+  Value range: 0-1 (`0.1` by default).
+
+[float]
+[[dfanalytics-dest-resources]]
+==== Dest configuration objects
+
+The `dest` configuration object has the following properties:
+
+`index` (Required)::
+  (string) The name of the index in which to store the results of the 
+  {dfanalytics-job}.
+
+`results_field` (Optional)::
+  (string) The name of the field in which to store the results of the analysis. 
+  The default value is `ml`.
+
+[float]
+[[dfanalytics-source-resources]]
+==== Source configuration objects
+
+The `source` configuration object has the following properties:
+
+`index` (Required)::
+  (array) An array of index names on which to perform the analysis. It can be a 
+  single index or index pattern as well as an array of indices or patterns.
+
+`query`::
+  (object) The {es} query domain-specific language (DSL). This value
+  corresponds to the query object in an {es} search POST body. All the
+  options that are supported by {es} can be used, as this object is
+  passed verbatim to {es}. By default, this property has the following
+  value: `{"match_all": {"boost": 1}}`.

docs/reference/ml/apis/evaluateresources.asciidoc

@@ -0,0 +1,63 @@
+[role="xpack"]
+[testenv="platinum"]
+[[ml-evaluate-dfanalytics-resources]]
+=== Evaluate {dfanalytics} resources
+
+ An evaluation configuration object has the following properties:
+
+`evaluation`::
+  (object) Defines the type of evaluation you want to perform. The value of this 
+  object can be different depending on the type of evaluation you want to 
+  perform. For more information, see <<ml-evaluation-types>>.
+
+
+[float]
+[[ml-evaluation-types]]
+==== Evaluation types
+
+
+[float]
+[[binary-sc-resources]]
+===== Binary soft classification configuration object
+
+Binary soft classification evaluates the results of an analysis which outputs 
+the probability that each {dataframe} row belongs to a certain class. For 
+example, in the context of outlier detection, the analysis outputs the 
+probability whether each row is an outlier.
+
+A binary soft classification object has the following properties:
+
+`actual_field` (Required)::
+  (string) The field of the `index` which contains the `ground 
+  truth`. The data type of this field can be boolean or integer. If the data 
+  type is integer, the value has to be either `0` (false) or `1` (true).
+
+`predicted_probability_field` (Required)::
+  (string) The field of the `index` that defines the probability of whether the 
+  item belongs to the class in question or not. It's the field that contains the 
+  results of the analysis.
+
+`metrics` (Optional)::
+  (object) Specifies the metrics that are used for the evaluation. Available 
+  mertics:
+
+  `auc_roc` (Optional)::
+    (object) The AUC ROC (area under the curve of the receiver operating 
+    characteristic) score and optionally the curve.
+    Default value is {"includes_curve": false}.
+
+  `precision` (Optional)::
+    (object) Set the different thresholds of the {olscore} at where the metric 
+    is calculated.
+    Default value is {"at": [0.25, 0.50, 0.75]}.
+
+  `recall` (Optional)::
+    (object) Set the different thresholds of the {olscore} at where the metric 
+    is calculated.
+    Default value is {"at": [0.25, 0.50, 0.75]}.
+
+  `confusion_matrix` (Optional)::
+    (object) Set the different thresholds of the {olscore} at where the metrics 
+    (TP - true positive, FP - false positive, TN - true negative, FN - false 
+    negative) are calculated.
+    Default value is {"at": [0.25, 0.50, 0.75]}.

docs/reference/rest-api/defs.asciidoc

@@ -8,6 +8,8 @@ These resource definitions are used in APIs related to {ml-features} and
 * <<ml-calendar-resource,Calendars>>
 * <<ml-datafeed-resource,{dfeeds-cap}>>
 * <<ml-datafeed-counts,{dfeed-cap} counts>>
+* <<ml-dfanalytics-resources,{dfanalytics-cap}>>
+* <<ml-evaluate-dfanalytics-resources,Evaluate {dfanalytics}>>
 * <<ml-filter-resource,Filters>>
 * <<ml-job-resource,Jobs>>
 * <<ml-jobstats,Job statistics>>
@@ -19,6 +21,8 @@ These resource definitions are used in APIs related to {ml-features} and
 
 include::{es-repo-dir}/ml/apis/calendarresource.asciidoc[]
 include::{es-repo-dir}/ml/apis/datafeedresource.asciidoc[]
+include::{es-repo-dir}/ml/apis/dfanalyticsresources.asciidoc[]
+include::{es-repo-dir}/ml/apis/evaluateresources.asciidoc[]
 include::{es-repo-dir}/ml/apis/filterresource.asciidoc[]
 include::{es-repo-dir}/ml/apis/jobresource.asciidoc[]
 include::{es-repo-dir}/ml/apis/jobcounts.asciidoc[]