Research and application of prediction model for returning home development population based on machine learning technology

Abstract

With the development of the Chinese economy and the increasing pressure of living in first-tier cities, more and more young people choose to return to their hometowns for development. To efficiently serve users and improve their product usage experience, the use of algorithms such as LightGBM and CatBoost was proposed to predict the returning population, thereby providing a basis for services and products, and improving user market retention rates.

Keywords

• LightGBM;feature engineering;<italic>K</italic>NN;<italic>K</italic>-fold cross-validation