Machine Learning-XGBoost Analysis of Re-employment Intention of Full-time Mothers

This study focused on the effects of social support from strong and weak relationships on the re-employment intention of full-time mothers after the implementation of the three-child birth policy in China. This study received 358 valid questionnaires, and utilized the XGBoost machine learning algorithm to create model. After conducting an optimal search for the network parameters, we achieved an accuracy of 97.22% on the test set. Furthermore, XGBoost can effectively rank the importance of independent variables, facilitating timely and effective prediction and adjustment of re-employment intention based on significant factors.