The aim of this project is to develop a predictive model for forecasting future sales based on historical sales data. By leveraging machine learning techniques, specifically the XGBoost algorithm, we ...

This repo contains the official implementation of the AISTATS 2024 paper Generating and Imputing Tabular Data via Diffusion and Flow-based XGBoost Models. To make it easily accessible, we release our ...

XGBoost, used in the handling of large datasets for supervised machine learning, has been given an overhaul in the new version 2.0.. The open source offering allows developers to fine-tune various ...

This paper aims to optimize the traditional XGBoost regression model by using the four-vector algorithm, so as to achieve the accurate prediction of road traffic flow. The main objective of the ...

XGBoost is a powerful gradient boosting algorithm that can effectively handle both categorical and continuous data. It stands out for its speed when predicting large datasets and offers a high degree ...