.. _MERMachineLearningModel:
  
Machine Learning Model Product
------------------------------
  
Data product name
=================
.. DataProductNameStart
   
DpdMerMachineLearningModel
   
.. DataProductNameEnd
   
Data product custodian
======================
.. DataProductCustodianStart
   
MER
   
.. DataProductCustodianEnd
   
Data model tag
==============
.. DataModelTagStart
   
9.0.2
   
.. DataModelTagEnd
   
Name of the Schema file
=======================
.. NameSchemaStart
   
euc-test-mer-MachineLearningModel.xsd
   
.. NameSchemaEnd
   
Schema documentation tag
========================
.. SchemaDocTagStart
   
:emphasis:`Documentation for data product element DpdMerMachineLearningModel:`
    
MER machine learning model. This product is an input to the MER processing
function. It contains a trained machine learning model used in one of the MER
processing steps.
   
.. SchemaDocTagEnd
   
Data product elements
=====================
.. DataProductElementsStart
   
Header of type: sys:genericHeader

Data of type: mer:merDqcMachineLearningModel

QualityFlags of type: dqc:sqfPlaceHolder

Parameters of type: ppr:genericKeyValueParameters

   
.. DataProductElementsEnd
   
Processing Element(s) creating/using the data product
=====================================================
.. PECreatorStart

Creators:

* None. This is an input product that is generated manually or using some
  dedicated scripts.
  
Consumers:
 
* This product is not used at the moment in the MER pipeline.

.. PECreatorEnd
   
Processing function using the data product
==========================================
.. PFUsingStart
   
MER

.. PFUsingEnd
   
Detailed description of the data product
========================================
.. DetailedDescStart

This product is an input to the MER :term:`Pipeline`. It contains a machine
learning model trained by the MER team and that will be used by one or several
of the MER processing steps (e.g. deblending, morphology).

The main elements inside this product are:

* **TileIndex** (optional): The MER tile index to which the machine learning
  model should be associated.
* **PatchId** (optional): The sky patch id to which the machine learning model
  should be associated.
* **ProcessingMode** (optional): The MER pipeline processing mode (WIDE or
  DEEP) to which the machine learning model should be associated.
* **Model**: The machine learning model type (e.g. Deblending, Morphology,
  SpuriousSources).
* **DataStorage**: Element that links to a file containing the machine learning 
  model data set.

.. DetailedDescEnd