An Empirical Study on Two-child Policy in China Based on Statistical Analysis and Machine Learning

DOI

10.2991/ssphe-18.2019.99How to use a DOI?

Keywords

Two-child policy, Statistical analysis, Imbalance classification, Machine learning, Hypotheses test

Abstract

Since the universal two-child policy (TCP) in China is launched in 2016, many researchers have dedicated their efforts into investigating the influences from the society point of view. In this paper, we look at this issue from a different angle, trying to investigate how the factors influence whether an expectant mother would bore a second child in China empirically. The real-world data from both rural and city regions are used to train an imbalance classification model. In addition, some statistical hypotheses are also made to justify the relevance of these factors. Experimental results demonstrate the validity and effectiveness of our trained model.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yizhou Chi
AU  - Xingyue Huang
AU  - Yu Zhou
PY  - 2019/01
DA  - 2019/01
TI  - An Empirical Study on Two-child Policy in China Based on Statistical Analysis and Machine Learning
BT  - Proceedings of the 2nd International Conference on Social Science, Public Health and Education (SSPHE 2018)
PB  - Atlantis Press
SP  - 430
EP  - 433
SN  - 2352-5398
UR  - https://doi.org/10.2991/ssphe-18.2019.99
DO  - 10.2991/ssphe-18.2019.99
ID  - Chi2019/01
ER  -