This paper focuses on the impact of Hangzhou’s allocation policies on school district housing. Using a multistage sampling method and stratified sampling method, the researchers selected a sample size and survey subjects from the original six districts in Hangzhou. A structured questionnaire and Likert scale method were used to design the survey questionnaire, and in-depth interview questions were designed based on the principles of in-depth interviews. After completing the distribution and acquisition of the questionnaire and the cleaning of the relevant data, the researchers used the multiple logistic regression model to study the significance of the eight factors that affect parents’ intention to buy a house, and then used various machine learning classification methods such as KNN, decision tree, Boosting, Bagging, and random forest, and calculated the influence of the influence variables on the intention to buy a house using 10-fold cross-validation. Based on this analysis, housing price differences in the three months before and after the policy were analyzed, and related policy recommendations were put forward. 

Yihan Ye, Xin Zhou, Peiying Zheng, Yujie Han, Xinsheng Ma. Research on the Impact of Hangzhou’s Allocation Policies on School District Housing Based on Machine Learning Algorithms. International Journal of New Developments in Education (2023) Vol. 5, Issue 1: 80-85. https://doi.org/10.25236/IJNDE.2023.050114.

[1] Mao F F, Luo G F, Pan J S. Research on the Impact of High-Quality Educational Resources on Housing Prices in Hangzhou School District [J]. Urban and Environmental Research, 2014, 1(02): 53-64. 

[2] Zhang Y. The Influence of Differentiation of Educational Resources on Real Estate Prices Taking Hangzhou West Lake District as an Example [D]. Hangzhou: Zhejiang University, 2015. 

[3] Huang Y. Research on Housing Heat in School Districts [D]. Changsha: Hunan Normal University, 2015. 

[4] Liu J C, Zhang L L. Analysis on the Phenomenon of “Housing Fever in School Districts” [J]. Educational Science Forum, 2011(12): 61-63. 

[5] Si S K, Sun X J. Mathematical Modeling Algorithms and Applications (3rd Edition) [M]. Beijing: National Defense Industry Press, 2021. 

[6] He X Q. Multivariate Statistical Analysis (Fifth Edition) [M]. Beijing: Renmin University of China Press, 2019. 

[7] Wang B H. Multivariate Statistical Analysis and R Language Modeling (Fifth Edition) [M]. Beijing: Higher Education Press, 2020. 

[8] Wu X Z, Zhang M. Applied Regression and Classification—Realization Based on R and Python [M]. Beijing: Renmin University of China Press, 2020. 

[9] Wei Z S. Probability Theory and Mathematical Statistics Course (Second Edition) [M]. Beijing: Higher Education Press, 2008.