Optimizing Machine Learning Models for Soil Fertility Analysis: Insights from Feature Engineering and Data Localization

Charles Onyeka Nwamekwe, Nnamdi Vitalis, Ewuzie, C. Okpala, Okechukwu Chiedu Ezeanyim, Chibuzo Victoria Nwabueze, Emeka Celestine Nwabunwanne

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DOI: 10.54287/gujsa.1605587
Published: 2025-03-26
Container: Gazi University Journal of Science Part A: Engineering and Innovation
Publisher: Gazi University
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.54287/gujsa.1605587,
  title = {Optimizing Machine Learning Models for Soil Fertility Analysis: Insights from Feature Engineering and Data Localization},
  author = {Charles Onyeka Nwamekwe and Nnamdi Vitalis, Ewuzie and C. Okpala and Okechukwu Chiedu Ezeanyim and Chibuzo Victoria Nwabueze and Emeka Celestine Nwabunwanne},
  year = {2025},
  journal = {Gazi University Journal of Science Part A: Engineering and Innovation},
  doi = {10.54287/gujsa.1605587},
  url = {https://doi.org/10.54287/gujsa.1605587}
}

RIS

TY  - JOUR
TI  - Optimizing Machine Learning Models for Soil Fertility Analysis: Insights from Feature Engineering and Data Localization
AU  - Charles Onyeka Nwamekwe
AU  - Nnamdi Vitalis, Ewuzie
AU  - C. Okpala
AU  - Okechukwu Chiedu Ezeanyim
AU  - Chibuzo Victoria Nwabueze
AU  - Emeka Celestine Nwabunwanne
PY  - 2025
JO  - Gazi University Journal of Science Part A: Engineering and Innovation
DO  - 10.54287/gujsa.1605587
UR  - https://doi.org/10.54287/gujsa.1605587
ER  -

APA

Nwamekwe, C. O., Ewuzie, N. V., Okpala, C., Ezeanyim, O. C., Nwabueze, C. V., & Nwabunwanne, E. C. (2025). Optimizing Machine Learning Models for Soil Fertility Analysis: Insights from Feature Engineering and Data Localization. Gazi University Journal of Science Part A: Engineering and Innovation. https://doi.org/10.54287/gujsa.1605587

Source records

crossref · retrieved 2026-09-25T10:17:02.616Z