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
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
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
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
1 Algorithm Introduction LightGBM (Light Gradient Boosting Machine, hereinafter referred to as LGBM) is an efficient and scalable machine learning algorithm based on Gradient Boosted Decision Trees (GBDT). As a member of the GBDT framework algorithms and a successor to the XGB algorithm, LGBM effectively integrates a series of advantages from previous GBDT algorithms, including … Read more
Every algorithm has its applicable range, and understanding its pros and cons can help avoid errors caused by inappropriate use. This article summarizes the pros and cons of common machine learning algorithms for reference. The sources are from “Machine Learning: Using R, Tidyverse, and mlr” (Algorithms 1 to 17) and “Neural Networks: Implementation in R” … Read more
Abstract: Stakeholder financial risk is one of the most socially harmful risks in financial risks. Effectively identifying stakeholder financial risks and safeguarding financial security is the core of financial risk prevention. In the field of stakeholder financial risk prevention, information extraction from multi-source heterogeneous data and the combination of data models are crucial. This article … Read more
The benefit of using ensemble decision tree methods like gradient boosting is that they can automatically provide estimates of feature importance from trained predictive models. In this article, you will discover how to estimate the importance of features for predictive modeling problems using the XGBoost library in Python. After reading this article, you will know: … Read more
Reference Paper Jianping Lin, Chengwei Qi, Hailang Wan, et al. Prediction of Cross-Tension Strength of Self-Piercing Riveted Joints Using Finite Element Simulation and XGBoost Algorithm. Chinese Journal of Mechanical Engineering, 2021 34: 36. Research Background and Purpose The use of high-strength aluminum alloys is an important means of lightweighting in automobiles. However, due to the … Read more
