[E&A] Removes anomaly detection and DFA content from the ML in Kibana section

explore-analyze/toc.yml

@@ -214,8 +214,6 @@ toc:
           - file: machine-learning/nlp/ml-nlp-limitations.md
       - file: machine-learning/machine-learning-in-kibana.md
         children:
-          - file: machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md
-          - file: machine-learning/machine-learning-in-kibana/xpack-ml-dfanalytics.md
           - file: machine-learning/machine-learning-in-kibana/xpack-ml-aiops.md
           - file: machine-learning/machine-learning-in-kibana/inference-processing.md
   - file: scripting.md

explore-analyze/visualize.md

@@ -29,9 +29,9 @@ $$$panels-editors$$$
 |  | [Image](visualize/image-panels.md) | Personalize your dashboard with custom images |
 |  | [Links](visualize/link-panels.md) | Add links to other dashboards or to external websites |
 |  | | |
-| Machine Learning and Analytics | [Anomaly swim lane](machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md) | Display the results from machine learning anomaly detection jobs |
-|  | [Anomaly chart](machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md) | Display an anomaly chart from the **Anomaly Explorer** |
-|  | [Single metric viewer](machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md) | Display an anomaly chart from the **Single Metric Viewer** |
+| Machine Learning and Analytics | [Anomaly swim lane](machine-learning/anomaly-detection/ml-ad-view-results.md) | Display the results from machine learning anomaly detection jobs |
+|  | [Anomaly chart](machine-learning/anomaly-detection/ml-ad-view-results.md) | Display an anomaly chart from the **Anomaly Explorer** |
+|  | [Single metric viewer](machine-learning/anomaly-detection/ml-ad-view-results.md) | Display an anomaly chart from the **Single Metric Viewer** |
 |  | [Change point detection](machine-learning/machine-learning-in-kibana/xpack-ml-aiops.md#change-point-detection) | Display a chart to visualize change points in your data |
 |  | | |
 | Observability | [SLO overview](/solutions/observability/incident-management/service-level-objectives-slos.md) | Visualize a selected SLO’s health, including name, current SLI value, target, and status |

redirects.yml

@@ -213,4 +213,8 @@ redirects:
   'manage-data/ingest/transform-enrich/ingest-pipelines-serverless.md': 'manage-data/ingest/transform-enrich/ingest-pipelines.md'
 
 # Related to https://github.com/elastic/docs-content/pull/2010
-  'manage-data/lifecycle/index-lifecycle-management/index-management-in-kibana.md': 'manage-data/data-store/index-basics.md'
+  'manage-data/lifecycle/index-lifecycle-management/index-management-in-kibana.md': 'manage-data/data-store/index-basics.md'
+
+  # Related to https://github.com/elastic/docs-content/pull/2097
+  'explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md': 'explore-analyze/machine-learning/anomaly-detection.md'
+  'explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-dfa-analytics.md': 'explore-analyze/machine-learning/data-frame-analytics.md'

solutions/observability/logs/inspect-log-anomalies.md

@@ -16,7 +16,7 @@ When the {{anomaly-detect}} features of {{ml}} are enabled, you can use the **Lo
 * A significant drop in the log rate might suggest that a piece of infrastructure stopped responding, and thus we’re serving fewer requests.
 * A spike in the log rate could denote a DDoS attack. This may lead to an investigation of IP addresses from incoming requests.
 
-You can also view log anomalies directly in the [{{ml-app}} app](/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md).
+You can also view log anomalies directly in the [{{ml-app}} app](/explore-analyze/machine-learning/anomaly-detection/ml-ad-view-results.md).
 
 ::::{note}
 This feature makes use of {{ml}} {{anomaly-jobs}}. To set up jobs, you must have `all` {{kib}} feature privileges for **{{ml-app}}**. Users that have full or read-only access to {{ml-features}} within a {{kib}} space can view the results of *all* {{anomaly-jobs}} that are visible in that space, even if they do not have access to the source indices of those jobs. You must carefully consider who is given access to {{ml-features}}; {{anomaly-job}} results may propagate field values that contain sensitive information from the source indices to the results. For more details, refer to [Set up {{ml-features}}](/explore-analyze/machine-learning/setting-up-machine-learning.md).