BO-XGBoost

Construction and Validation of Prognostic Models for Sepsis-Associated Acute Kidney Injury

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Construction and Validation of Prognostic Models for Sepsis-Associated Acute Kidney Injury

Acute Kidney Injury (AKI) is a common complication in critically ill patients with sepsis, often associated with poor prognosis. This study aims to construct and validate an interpretable prognostic prediction model for sepsis-associated AKI (S-AKI) patients using machine learning (ML) methods. The training cohort data was sourced from the MIMIC-IV database, and the external validation … Read more

Pretest Probability Model for Obstructive Coronary Artery Disease Based on Machine Learning

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Pretest Probability Model for Obstructive Coronary Artery Disease Based on Machine Learning

Click the blue WeChat name under the title to quickly follow This article is published in: Chinese Journal of Internal Medicine, 2022, 61(2): 185-192. Authors: Wang Kai, Yang Junjie, Liu Ziwan, Dou Guanhua, Wang Xi, Shan Dongkai, Chen Yundai Abstract Objective To develop a pretest probability model for obstructive coronary artery disease in the Chinese … Read more

Hourly Natural Gas Load Forecasting Based on STL-XGBoost-NBEATSx

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Hourly Natural Gas Load Forecasting Based on STL-XGBoost-NBEATSx

1. Author Information Authors: Shao Bilin, Ren Meng, Tian Ning Affiliation: School of Management, Xi’an University of Architecture and Technology, Xi’an, Shaanxi 710311 Author Biography: Shao Bilin (1965-), male, professor, master’s supervisor, doctoral supervisor, research interests include big data, artificial intelligence, data information and management, energy sustainable development. E-mail: [email protected] Corresponding Author: Ren Meng (1999-), … Read more

Detection of False Data Injection Attacks Using Unsupervised and Supervised Learning

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Detection of False Data Injection Attacks Using Unsupervised and Supervised Learning

Reference Information (Click Title to Read Full Text) Huang Dongmei, Wang Yifan, Hu Anduo, et al. Detection method of false data injection attack based on unsupervised and supervised learning[J]. Electric Power Engineering Technology, 2024, 43(2):134-141. HUANG Dongmei, WANG Yifan, HU Anduo, et al. Detection method of false data injection attack based on unsupervised and supervised … Read more

Research on Financial Fraud Prediction Model of Listed Companies Based on XGBoost

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Research on Financial Fraud Prediction Model of Listed Companies Based on XGBoost

Author Introduction Zhou Weihua，Institute of Digital Finance, Chinese Academy of Fiscal Sciences Zhai Xiaofeng，Institute of Digital Finance, Chinese Academy of Fiscal Sciences Tan Haowei，Institute of Digital Finance, Chinese Academy of Fiscal Sciences Research on Financial Fraud Prediction Model of Listed Companies Based on XGBoost Research Background In recent years, the Central Committee of the Communist … Read more

Summary of Hessian Matrix Applications in XGBoost Algorithm

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Summary of Hessian Matrix Applications in XGBoost Algorithm

Introduction The most common application of the Hessian matrix is in the Newton optimization method, which mainly seeks the extremum points of a function where the first derivative is zero. This article provides a straightforward summary of the two applications of the Hessian matrix in the XGBoost algorithm, namely the minimum child weight algorithm and … Read more