Proceedings of the 2nd International Conference on Social Science, Public Health and Education (SSPHE 2018)

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

Authors
Yizhou Chi, Xingyue Huang, Yu Zhou
Corresponding Author
Yu Zhou
Available Online January 2019.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2nd International Conference on Social Science, Public Health and Education (SSPHE 2018)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
January 2019
ISBN
978-94-6252-653-2
ISSN
2352-5398
DOI
https://doi.org/10.2991/ssphe-18.2019.99How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 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  - https://doi.org/10.2991/ssphe-18.2019.99
ID  - Chi2019/01
ER  -