Data for: Orthogonal Procrustes and Machine Learning: Predicting Bill of Material Errors on Time

Published: 17 April 2023| Version 3 | DOI: 10.17632/wspxdsnmh3.3
Contributor:
Simon Schramm

Description

A detailed description can be found in the README file.

Files

Steps to reproduce

Download all of the specified files and run main.py to start the pipeline. Further information can be found in the README file.

Categories

Computer Science, Artificial Intelligence, Artificial Neural Networks, Clustering

Funding

BMW Group

Licence