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Modelling children ever born using performance evaluation metrics: A dataset

Predicting the number of total children ever born in a country is a key component for proper implementation of economic growth policy. Here, performance metrics were used to predict models that appropriately describe the factors that affect children ever born. A comparison of 60% training and 40% va...

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Detalles Bibliográficos
Autores principales: Ibeji, Jecinta U., Zewotir, Temesgen, North, Delia, Amusa, Lateef
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134711/
https://www.ncbi.nlm.nih.gov/pubmed/34026975
http://dx.doi.org/10.1016/j.dib.2021.107077
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author Ibeji, Jecinta U.
Zewotir, Temesgen
North, Delia
Amusa, Lateef
author_facet Ibeji, Jecinta U.
Zewotir, Temesgen
North, Delia
Amusa, Lateef
author_sort Ibeji, Jecinta U.
collection PubMed
description Predicting the number of total children ever born in a country is a key component for proper implementation of economic growth policy. Here, performance metrics were used to predict models that appropriately describe the factors that affect children ever born. A comparison of 60% training and 40% validation, 70% training and 30% validation, 80% training and 20% validation also 90% training and 10% validation was performed respectively to examine the three models’ behaviours (Poisson regression, Negative Binomial regression and Generalized Poisson regression) with RMSE, R(2), MAE and MSE as performance metrics. Although all the three models had almost identical performance evaluation metrics, the Poisson regression was chosen as the most appropriate model because it is the simplest model.
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spelling pubmed-81347112021-05-21 Modelling children ever born using performance evaluation metrics: A dataset Ibeji, Jecinta U. Zewotir, Temesgen North, Delia Amusa, Lateef Data Brief Data Article Predicting the number of total children ever born in a country is a key component for proper implementation of economic growth policy. Here, performance metrics were used to predict models that appropriately describe the factors that affect children ever born. A comparison of 60% training and 40% validation, 70% training and 30% validation, 80% training and 20% validation also 90% training and 10% validation was performed respectively to examine the three models’ behaviours (Poisson regression, Negative Binomial regression and Generalized Poisson regression) with RMSE, R(2), MAE and MSE as performance metrics. Although all the three models had almost identical performance evaluation metrics, the Poisson regression was chosen as the most appropriate model because it is the simplest model. Elsevier 2021-04-22 /pmc/articles/PMC8134711/ /pubmed/34026975 http://dx.doi.org/10.1016/j.dib.2021.107077 Text en © 2021 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Ibeji, Jecinta U.
Zewotir, Temesgen
North, Delia
Amusa, Lateef
Modelling children ever born using performance evaluation metrics: A dataset
title Modelling children ever born using performance evaluation metrics: A dataset
title_full Modelling children ever born using performance evaluation metrics: A dataset
title_fullStr Modelling children ever born using performance evaluation metrics: A dataset
title_full_unstemmed Modelling children ever born using performance evaluation metrics: A dataset
title_short Modelling children ever born using performance evaluation metrics: A dataset
title_sort modelling children ever born using performance evaluation metrics: a dataset
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134711/
https://www.ncbi.nlm.nih.gov/pubmed/34026975
http://dx.doi.org/10.1016/j.dib.2021.107077
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