.. _SHEMomentsMLTraining:

Shear MomentsML Training
------------------------

$SetSchemaPath she/euc-she-MomentsMlTraining.xsd 

Data product name
=================
.. DataProductNameStart

$PrintDataProductName

.. DataProductNameEnd

Data product custodian
======================
.. DataProductCustodianStart
   
$PrintDataProductCustodian
   
.. DataProductCustodianEnd
      
Name of the Schema file
=======================
.. NameSchemaStart
   
$PrintSchemaFilename
   
.. NameSchemaEnd

Last Edited for DPDD Version
____________________________
.. DpddVersionTagStart

1.1

.. DpddVersionTagEnd

Data product elements
=====================
.. DataProductElementsStart

$PrintDataProductElements

.. DataProductElementsEnd

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

SHE

.. PECreatorEnd

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

SHE

.. PFUsingEnd

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

An XML data product containing trained parameters of the MomentsML shear measurement algorithm.
The data consists mainly of parameters (weights and biases) of artificial neural networks trained to predict shear, and of a description of the architecture of these networks.
Given the complex structure of this data, it is serialized into an binary file, in a format supported by the TensorFlow and Keras libraries.

For MomentsML, the distinction between "training" and "calibration" is that training refers to the optimization of the machine-learning model itself, while calibration offers a possibility to address effects not captured by the training simulations of the machine learning.

.. DetailedDescEnd