machine learning rst

Change-Id: I0eb7f709ac5f44c40b34271def2bf5a69283d48e

doc/source/contributor/configuration.rst

@@ -36,3 +36,13 @@ Notifiers
    nova-notifier
    notifier-snmp-plugin
    mistral-config
+
+
+Machine_Learning
+----------------
+
+.. toctree::
+   :maxdepth: 1
+
+   ml-jaccard_correlation
+

doc/source/contributor/ml-jaccard_correlation.rst

@@ -0,0 +1,56 @@
+======================================================
+Vitrage Machine Learning plugins - Jaccard Correlation
+======================================================
+
+Overview
+========
+
+Machine Learning algorithms can contribute to Vitrages' purposes. The `Jaccard
+Correlation <http://en.wikipedia.org/wiki/Jaccard_index>`_
+plugin was created in order to calculate correlations between
+alarms, to recommend the client on new templates for better predicting alarms
+and better RCA in the future.
+
+This document describes the usage of the Machine Learning service plugin -
+Jaccard Correlation.
+
+Machine Learning service configuration
+--------------------------------------
+In ``/etc/vitrage/vitrage.conf``:
+
+Activate the plugins to be used:
+
+[machine_learning]
+
+plugins = jaccard_correlation
+
+**   In order to use different plugin, insert plugin names separated by commas.
+
+
+Jaccard Correlation plugin configuration
+----------------------------------------
+
+1. This plugin calculates correlations for each pair of alarms, while an alarm
+defined as (alarm name, resource type).
+
+   The output is a report, generated once in 'num_of_events_to_flush', with
+   correlation score for each pair of alarms, sorted by correlation score.
+   For now, the report only shows correlations but not causality.
+
+2. In ``/etc/vitrage/vitrage.conf``:
+
+   Configure Jaccard Correlations plugin:
+
+   [jaccard_correlation]
+
+   num_of_events_to_flush = ``<number of events to catch before flushing
+   saved data, by default 1000>``
+
+   output_folder = ``<the folder to which reports will be saved, by default /tmp>``
+
+   correlation_threshold = ``<all alarms pairs with correlation score above
+   threshold will appear in the report, the default is 0>``
+
+   high_corr_score = ``<high correlation threshold, by default 0.9>``
+
+   med_corr_score = ``<medium correlation score threshold, 0.5 by default>``