Using an interpretable Machine Learning approach to study the drivers of International Migration

Kiossou, Harold Silvère; Schenk, Yannik; Docquier, Fredérić; Houndji, Vinasétan Ratheil; Nijssen, Siegfried; Schaus, Pierre

doi:10.48550/arxiv.2006.03560

Cited by 2 publications

(2 citation statements)

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“…Subsequently, to improve the interpretability of machine-learning models, Kiossou et al used an interpretable machine-learning approach to study the drivers of international migration with greater accuracy than the classical gravity model [104]. This approach also provides a deeper understanding of how migration is affected by drivers, effectively revealing the non-linear relationship between covariates and outcome variables.…”

Section: Classical Machine-learning Prediction Methods 1 Artificial N...mentioning

confidence: 99%

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Huang

Yang

et al. 2023

Sustainability

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As a fundamental, holistic, and strategic issue facing human society, human migration is a key factor affecting the development of countries and cities, given the constantly changing population numbers. The fuzziness of the spatiotemporal attributes of human migration limits the pool of open-source data for human migration prediction, leading to a relative lag in human migration prediction algorithm research. This study expands the definition of human migration research, reviews the progress of research into human migration prediction, and classifies and compares human migration algorithms based on open-source data. It also explores the critical uncertainty factors restricting the development of human migration prediction. Based on the analysis, there is no “best” migration prediction model, and data are key to forecasting human migration. Social media’s popularity and its increase in data have enabled the application of artificial intelligence in population migration prediction, which has attracted the attention of researchers and government administrators. Future research will aim to incorporate uncertainty into the predictive analysis framework, and explore the characteristics of population migration behaviors and their interactions. The integration of machine-learning and traditional data-driven models will provide a breakthrough for this purpose.

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Section: Classical Machine-learning Prediction Methods 1 Artificial N...mentioning

confidence: 99%

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Huang

Yang

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…Subsequently, to improve the interpretability of machine learning models, Kiossou et al used an interpretable machine learning approach to study the drivers of international migration with higher accuracy than the classical gravity model [100]. It also provides a deeper understanding of how migration is affected by its drivers, effectively revealing the interesting non-linear relationship between covariates and outcome variables.…”

Section: Machine Learning Prediction Methodsmentioning

confidence: 99%

Transcending Time and Space: A Survey Methods, Uncertainty, and Development in Human Migration Prediction

Pu¹,

Huang²,

Yang³

et al. 2023

Preprint

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As a fundamental, overall, and strategic issue facing human society, human migration is a key factor affecting the development of countries and cities given constantly changing population numbers. The fuzziness of the spatiotemporal attributes of human migration limits the pool of open-source data for human migration prediction, leading to a relative lag in human migration prediction algorithm research. This study expands the definition of human migration research, reviews the progress of research into human migration prediction, and classifies and compares human migration algorithms based on open-source data. It also explores the critical uncertainty factors restricting the development of human migration prediction. Given the effect of human migration prediction, in combination with artificial intelligence and big data technology, the paper concludes with specific suggestions and countermeasures aimed at enhancing human migration prediction research results to serve economic and social development and national strategy.

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Using an interpretable Machine Learning approach to study the drivers of International Migration

Cited by 2 publications

References 0 publications

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Transcending Time and Space: A Survey Methods, Uncertainty, and Development in Human Migration Prediction

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