Shear MomentsML Training

$SetSchemaPath she/euc-she-MomentsMlTraining.xsd

Data product name

$PrintDataProductName

Data product custodian

$PrintDataProductCustodian

Name of the Schema file

$PrintSchemaFilename

Last Edited for DPDD Version

1.1

Data product elements

$PrintDataProductElements

Processing Element(s) creating/using the data product

SHE

Processing function using the data product

SHE

Detailed description of the data product

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.