An Empirical Study on Two-child Policy in China Based on Statistical Analysis and Machine Learning
- 10.2991/ssphe-18.2019.99How to use a DOI?
- Two-child policy, Statistical analysis, Imbalance classification, Machine learning, Hypotheses test
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.
- © 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/).
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 - 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 -