Extreme Gradient Boosting

Extreme Gradient Boosting (XGBoost) is a powerful machine learning algorithm used for both classification and regression tasks, primarily focused on improving prediction accuracy and efficiency. Current research emphasizes XGBoost's application across diverse fields, including healthcare (predicting disease progression), engineering (monitoring infrastructure), and finance (forecasting market crises), often in comparison with other boosting algorithms like CatBoost and LightGBM, or even deep learning methods. Its success stems from its ability to handle complex datasets, provide interpretable results (through feature importance analysis), and achieve high predictive performance, making it a valuable tool for various scientific and practical applications.

Papers

November 3, 2024

Reconstructing MODIS Normalized Difference Snow Index Product on Greenland Ice Sheet Using Spatiotemporal Extreme Gradient Boosting Model
Fan Ye, Qing Cheng, Weifeng Hao, Dayu Yu
Reference Dataset Landsat 8 Extreme Gradient Boosting Ice Sheet Spatial Gradient

October 25, 2024

Less is More: Extreme Gradient Boost Rank-1 Adaption for Efficient Finetuning of LLMs
Yifei Zhang, Hao Zhu, Aiwei Liu, Han Yu, Piotr Koniusz, Irwin King
Large Language Model Fine Tuning High Efficiency Adaptation Concern Low Rank Adaptation Token Boosting Extreme Gradient Boosting

September 24, 2024

Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling
Henry Musto, Daniel Stamate, Doina Logofatu, Daniel Stahl
Mild Cognitive Impairment Cognitive Decline Extreme Gradient Boosting Cox Model Dementia Risk Deterioration Prediction

July 26, 2024

Supervised Learning based Method for Condition Monitoring of Overhead Line Insulators using Leakage Current Measurement
Mile Mitrovic, Dmitry Titov, Klim Volkhov, Irina Lukicheva, Andrey Kudryavzev, Petr Vorobev, Qi Li, Vladimir Terzija
Supervised Learning Practical Method Condition Monitoring Extreme Gradient Boosting Low Voltage Line Insulator Leakage Detector

May 28, 2024

Use of Boosting Algorithms in Household-Level Poverty Measurement: A Machine Learning Approach to Predict and Classify Household Wealth Quintiles in the Philippines
Erika Lynet Salvador
Machine Learning Model Machine Learning Approach Gradient Boosting Boosting Algorithm Extreme Gradient Boosting Poverty Level Adaptive Boosting Wealth Distribution Poverty Prediction

January 9, 2024

Music Genre Classification: A Comparative Analysis of CNN and XGBoost Approaches with Mel-frequency cepstral coefficients and Mel Spectrograms
Yigang Meng
Acoustic Feature XGBoost Model Music Classification Music Similarity Extreme Gradient Boosting MEL Spectrogram

January 6, 2024

CRISIS ALERT:Forecasting Stock Market Crisis Events Using Machine Learning Methods
Yue Chen, Xingyi Andrew, Salintip Supasanya
Machine Learning Stock Market Indian Stock Market Crisis Event Extreme Gradient Boosting

December 17, 2023

Analisis Eksploratif Dan Augmentasi Data NSL-KDD Menggunakan Deep Generative Adversarial Networks Untuk Meningkatkan Performa Algoritma Extreme Gradient Boosting Dalam Klasifikasi Jenis Serangan Siber
K. P. Santoso, F. A. Madany, H. Suryotrisongko
Generative Adversarial Network Data Augmentation GAN Model Extreme Gradient Boosting NSL KDD

August 12, 2023

Digital elevation model correction in urban areas using extreme gradient boosting, land cover and terrain parameters
Chukwuma Okolie, Jon Mills, Adedayo Adeleke, Julian Smit
Urban Environment Land Cover XGBoost Model Extra Gradient Extreme Gradient Boosting Digital Elevation Model Terrain Topology

August 2, 2023

Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features
Filipe A. C. Oliveira, Felipe M. Dias, Marcelo A. F. Toledo, Diego A. C. Cardenas, Douglas A. Almeida, Estela Ribeiro, Jose E. Krieger, Marco A. Gutierrez
New Machine PPG Signal Photoplethysmography Data Extreme Gradient Boosting Photoplethysmography Signal

July 15, 2023

Enhanced Gradient Boosting for Zero-Inflated Insurance Claims and Comparative Analysis of CatBoost, XGBoost, and LightGBM
Banghee So
XGBoost Model LightGBM Model Extreme Gradient Boosting Insurance Data Actuarial Model Zero Inflated Catboost Model Claim Frequency

April 23, 2023

Quantile Extreme Gradient Boosting for Uncertainty Quantification
Xiaozhe Yin, Masoud Fallah-Shorshani, Rob McConnell, Scott Fruin, Yao-Yi Chiang, Meredith Franklin
Uncertainty Quantification Quantile Regression Extreme Gradient Boosting

April 15, 2023

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates
Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane
Learning Rate Decentralized Data XGBoost Model Tree Ensemble Extreme Gradient Boosting Federated Gradient Boosting

November 15, 2022

Behavior of Hyper-Parameters for Selected Machine Learning Algorithms: An Empirical Investigation
Anwesha Bhattacharyya, Joel Vaughan, Vijayan N. Nair
Neural Network Machine Learning Empirical Study Machine Learning Algorithm BEHAVIOR Explanation Hyper Parameter Extreme Gradient Boosting ML Algorithm

October 3, 2022

Diagnosis of Parkinson's Disease Based on Voice Signals Using SHAP and Hard Voting Ensemble Method
Paria Ghaheri, Hamid Nasiri, Ahmadreza Shateri, Arman Homafar
Medical Diagnosis Parkinson Disease Gradient Boosting Extreme Gradient Boosting Voting Ensemble

August 26, 2022

Extreme Gradient Boosting for Yield Estimation compared with Deep Learning Approaches
Florian Huber, Artem Yushchenko, Benedikt Stratmann, Volker Steinhage
Deep Learning Satellite Image Yield Prediction Extreme Gradient Boosting Crop Development

August 5, 2022

A Computational Exploration of Emerging Methods of Variable Importance Estimation
Louis Mozart Kamdem, Ernest Fokoue
Random Forest Support Vector Machine New Method Variable Importance Extreme Gradient Boosting

April 15, 2022

Accurate ADMET Prediction with XGBoost
Hao Tian, Rajas Ketkar, Peng Tao
XGBoost Model Extreme Gradient Boosting ADMET Prediction

February 10, 2022

Quantune: Post-training Quantization of Convolutional Neural Networks using Extreme Gradient Boosting for Fast Deployment
Jemin Lee, Misun Yu, Yongin Kwon, Taeho Kim
Convolutional Neural Network Quantization Operator Post Training Quantization Multiplier Free Quantization Convolutional Neural Network Model Real Time Deployment Extreme Gradient Boosting

Extreme Gradient Boosting

Papers

Reconstructing MODIS Normalized Difference Snow Index Product on Greenland Ice Sheet Using Spatiotemporal Extreme Gradient Boosting Model

Less is More: Extreme Gradient Boost Rank-1 Adaption for Efficient Finetuning of LLMs

Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling

Supervised Learning based Method for Condition Monitoring of Overhead Line Insulators using Leakage Current Measurement

Use of Boosting Algorithms in Household-Level Poverty Measurement: A Machine Learning Approach to Predict and Classify Household Wealth Quintiles in the Philippines

Music Genre Classification: A Comparative Analysis of CNN and XGBoost Approaches with Mel-frequency cepstral coefficients and Mel Spectrograms

CRISIS ALERT:Forecasting Stock Market Crisis Events Using Machine Learning Methods

Analisis Eksploratif Dan Augmentasi Data NSL-KDD Menggunakan Deep Generative Adversarial Networks Untuk Meningkatkan Performa Algoritma Extreme Gradient Boosting Dalam Klasifikasi Jenis Serangan Siber

Digital elevation model correction in urban areas using extreme gradient boosting, land cover and terrain parameters

Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features

Enhanced Gradient Boosting for Zero-Inflated Insurance Claims and Comparative Analysis of CatBoost, XGBoost, and LightGBM

Quantile Extreme Gradient Boosting for Uncertainty Quantification

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates

Behavior of Hyper-Parameters for Selected Machine Learning Algorithms: An Empirical Investigation

Diagnosis of Parkinson's Disease Based on Voice Signals Using SHAP and Hard Voting Ensemble Method

Extreme Gradient Boosting for Yield Estimation compared with Deep Learning Approaches

A Computational Exploration of Emerging Methods of Variable Importance Estimation

Accurate ADMET Prediction with XGBoost

Quantune: Post-training Quantization of Convolutional Neural Networks using Extreme Gradient Boosting for Fast Deployment