Title: A novel fertility intention prediction scheme based on Naive Bayes

Authors: Meijiao Zhang; Lan Yang; Weiping Jiang; Gejing Xu; Guoliang Hu

Addresses: School of Software, Quanzhou University of Information Engineering, Quanzhou, Fujian, China ' School of Software, Quanzhou University of Information Engineering, Quanzhou, Fujian, China ' School of Computer Science and Engineering, Hunan University of Science and Technology, XiangTan, Hunan, China ' School of Software, Quanzhou University of Information Engineering, Quanzhou, Fujian, China ' Hunan Branch of National Computer Network Emergency Response, Technical Team/Coordination Center of China, Changsha, Hunan, China

Abstract: In today's society, the problem of ageing has developed into a global problem. The ageing of the population is related to the decrease in fertility intention. Therefore, it is meaningful to predict the fertility intention of people. In this paper, we propose a fertility intention prediction scheme based on a polynomial Naive Bayesian model, called the FPB scheme. In the proposed scheme, we first extract various features from the data we collected, and we divide the entire dataset into three labels according to the level of fertility intention. Then, we use these data to construct a classifier. Next, we use this classifier to design a perfect prediction algorithm to predict fertility intention. Finally, we conduct extensive experiments to evaluate the performance of the proposed scheme. The experimental results show that the proposed FPB scheme has high accuracy and can help families make accurate fertility decisions.

Keywords: fertility intention; polynomial Naive Bayes; prediction algorithm.

DOI: 10.1504/IJCSE.2025.143460

International Journal of Computational Science and Engineering, 2025 Vol.28 No.1, pp.1 - 9

Received: 13 Jul 2022
Received in revised form: 09 Aug 2022
Accepted: 20 Sep 2022
Published online: 21 Dec 2024 *

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