On the Comparative Study of the Supervised Machine Learning Models.

Asogwa O. C.; Eze N. M.; Christopher C. C.; Aruah K. E.; Chimezie I. E.

doi:10.52589/AJMSS-ILF4K7JB

On the Comparative Study of the Supervised Machine Learning Models. | AB Journals

On the Comparative Study of the Supervised Machine Learning Models.

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African Journal of Mathematics and Statistics Studies

Vol. 7Issue 42024pp. 162–173Published 14 November 2024

DOI 10.52589/AJMSS-ILF4K7JB

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Abstract:

This research empirically compared the performance of three supervised machine learning models which are Multinomial Logistic Regression (MLR), Multilayer back propagated Neural Networks (MNN) and Multinomial Decision Trees (MDT) based on a tested data set for the opinion of Nigerian citizens during the period of naira redesign policy using classification matrix criterion. About 600 copies of questionnaires on the opinion of Nigeria citizens on their individual welfare at the period of naira redesign. The result showed that, ANN outperformed other models with 94.4% correct classification rates, followed by the MLR with correctly classification rates of 93.5% and lastly by MDT with correct classification rates of 90.0%.

Keywords:Supervised machine learning Algorithm Naira redesign Classification rates Models.

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