Machine Learning Approach for National Innovation Performance Data Analysis

Dominik Forner, Sercan Ozcan, David Bacon

Abstract

National innovation performance is essential for being economically competitive. The key determinants for its increase or decrease and the impact of governmental decisions or policy instruments are still not clear. Recent approaches are either limited due to qualitatively selected features or due to a small database with few observations. The aim of this paper is to propose a suitable machine learning approach for national innovation performance data analysis. We use clustering and correlation analysis, Bayesian Neural Network with Local Interpretable Model-Agnostic Explanations and BreakDown for decomposing innovation output prediction. Our results show, that the machine learning approach is appropriate to benchmark national innovation profiles, to identify key determinants on a cluster as well as on a national level whilst considering correlating features and long term effects and the impact of changes in innovation input (e.g. by governmental decision or innovation policy) on innovation output can be predicted and herewith the increase or decrease of national innovation performance.

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Paper Citation


in Harvard Style

Forner D., Ozcan S. and Bacon D. (2019). Machine Learning Approach for National Innovation Performance Data Analysis.In Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-377-3, pages 325-331. DOI: 10.5220/0007953603250331


in Bibtex Style

@conference{data19,
author={Dominik Forner and Sercan Ozcan and David Bacon},
title={Machine Learning Approach for National Innovation Performance Data Analysis},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2019},
pages={325-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007953603250331},
isbn={978-989-758-377-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Machine Learning Approach for National Innovation Performance Data Analysis
SN - 978-989-758-377-3
AU - Forner D.
AU - Ozcan S.
AU - Bacon D.
PY - 2019
SP - 325
EP - 331
DO - 10.5220/0007953603250331