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Interpretable Machine-Learning Approach in Estimating FDI Inflow: Visualization of ML Models with LIME and H2O Cover

Interpretable Machine-Learning Approach in Estimating FDI Inflow: Visualization of ML Models with LIME and H2O

TalTech Journal of European Studies
Volume 11 (2021): Issue 1 (May 2021)
By: Devesh Singh  
Open Access
|May 2021

Authors

Devesh Singh

Dev.singh.ece@gmail.com

University of Kaposvár, Hungary
DOI: https://doi.org/10.2478/bjes-2021-0009 | Journal eISSN: 2674-4619 | Journal ISSN: 2674-4600
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Language: English
Page range: 133 - 152
Published on: May 26, 2021
Published by: Tallinn University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
FDI,
H2O,
local interpretable model-agnostic explanations,
machine learning
Related subjects:
Business and economics,
Political economics,
Political economics, other,
Computer sciences,
Computer sciences, other,
Law,
Law, other,
Social sciences,
Social sciences, other

© 2021 Devesh Singh, published by Tallinn University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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