A New Process Model for the Comprehensive Management of Machine Learning Models

Christian Weber, Pascal Hirmer, Peter Reimann, Holger Schwarz

2019

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 Harvard Style

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


in Bibtex Style

@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},
}


in EndNote Style

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