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Authors: Christian Weber 1 ; Pascal Hirmer 2 ; Peter Reimann 1 and Holger Schwarz 2

Affiliations: 1 Graduate School advanced Manufacturing Engineering, University of Stuttgart, Nobelstraße 12, 70569 Stuttgart and Germany ; 2 Institute for Parallel and Distributed Systems, University of Stuttgart, 70569 Stuttgart and Germany

ISBN: 978-989-758-372-8

Keyword(s): Model Management, Machine Learning, Analytics Process.

Abstract: The management of machine learning models is an extremely challenging task. Hundreds of prototypical models are being built and just a few are mature enough to be deployed into operational enterprise information systems. The lifecycle of a model includes an experimental phase in which a model is planned, built and tested. After that, the model enters the operational phase that includes deploying, using, and retiring it. The experimental phase is well known through established process models like CRISP-DM or KDD. However, these models do not detail on the interaction between the experimental and the operational phase of machine learning models. In this paper, we provide a new process model to show the interaction points of the experimental and operational phase of a machine learning model. For each step of our process, we discuss according functions which are relevant to managing machine learning models.

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Paper citation in several formats:
Weber, C.; Hirmer, P.; Reimann, P. and Schwarz, H. (2019). A New Process Model for the Comprehensive Management of Machine Learning Models.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 415-422. DOI: 10.5220/0007725304150422

@conference{iceis19,
author={Christian Weber. and Pascal Hirmer. and Peter Reimann. and Holger Schwarz.},
title={A New Process Model for the Comprehensive Management of Machine Learning Models},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={415-422},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007725304150422},
isbn={978-989-758-372-8},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A New Process Model for the Comprehensive Management of Machine Learning Models
SN - 978-989-758-372-8
AU - Weber, C.
AU - Hirmer, P.
AU - Reimann, P.
AU - Schwarz, H.
PY - 2019
SP - 415
EP - 422
DO - 10.5220/0007725304150422

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