3 papers
cs.LG2025
Gradient Boosting Decision Tree with LSTM for Investment Prediction
Chang Yu, Fang Liu, Jie Zhu +5
This paper proposes a hybrid framework combining LSTM (Long Short-Term Memory) networks with LightGBM and CatBoost for stock price prediction. The framework processes time-series f…
cs.CE2024
Application of an ANN and LSTM-based Ensemble Model for Stock Market Prediction
Fang Liu, Shaobo Guo, Qianwen Xing +5
Stock trading has always been a key economic indicator in modern society and a primary source of profit for financial giants such as investment banks, quantitative trading firms, a…
cs.LG2024
Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN
Chang Yu, Yixin Jin, Qianwen Xing +3
Bank credit risk is a significant challenge in modern financial transactions, and the ability to identify qualified credit card holders among a large number of applicants is crucia…