Results 121 to 130 of about 150,441 (331)

A Comparative Analysis of XGBoost

, 2019
XGBoost is a scalable ensemble technique based on gradient boosting that has demonstrated to be a reliable and efficient machine learning challenge solver. This work proposes a practical analysis of how this novel technique works in terms of training speed, generalization performance and parameter setup.
Bentéjac, Candice, Csörgő, Anna, Martínez-Muñoz, Gonzalo   +2 more
openaire   +2 more sources

OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley   +1 more source

Robust Decision Trees Against Adversarial Examples

, 2019
Although adversarial examples and model robustness have been extensively studied in the context of linear models and neural networks, research on this issue in tree-based models and how to make tree-based models robust against adversarial examples is ...
Boning, Duane, Chen, Hongge, Hsieh, Cho-Jui, Zhang, Huan   +3 more
core  

Predicting Order Status using XGBoost

, 2022
Invista, a Koch subsidiary, is a multinational producer of fibers, resins, and intermediaries, particularly nylon. To keep the company operating required them to take over 1.5 million orders over the course of - years, less than a third of which arrived on-time. Orders arriving other than when expected can cause many problems for any company.
openaire   +2 more sources

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

Advanced Intelligent Systems, EarlyView.
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov, Hanzhi Ma, Junbo Peng, Huifeng Dong, Jiangshan Zhuo, Mengke Shi, Lvting Wang, Shengchao Jiang, Ye Shi   +8 more
wiley   +1 more source

Machine Learning‐Driven Digital Twin of a Field‐Effect Transistor‐Based Hormone Biosensor for Real‐Time Estradiol Monitoring

Advanced Intelligent Systems, EarlyView.
A machine learning‐driven digital twin simulates an aptamer‐functionalized BioFET measuring 17β‐estradiol. Real‐time Isd signals are processed, features are extracted, and trained models estimate hormone concentration. In parallel, a one‐step‐ahead forward model learns biosensor dynamics and generates realistic synthetic signals, enabling in silico ...
Anastasiia Gorelova, Alexandra Parichenko, Shirong Huang, Santiago Melia, Gianaurelio Cuniberti   +4 more
wiley   +1 more source

COMPARISON OF XGBOOST AND RANDOM FOREST METHODS IN PREDICTING AIR POLLUTION LEVELS

Barekeng
Air is one of the elements needed by living things, including humans, to survive. The air quality in an area also affects the health and quality of human life and its surrounding environment.
Akas Yekti Pulih Asih, Firman Yudianto, Puguh Triwinanto, Rachman Sinatriya Marjianto, Teguh Herlambang, Hamzah Arof   +5 more
doaj   +1 more source

Integration of machine learning XGBoost and SHAP models for NBA game outcome prediction and quantitative analysis methodology

PLoS ONE
This study investigated the application of artificial intelligence in real-time prediction of professional basketball games, identifying the variations within performance indicators that are critical in determining the outcomes of the games.
Ouyang Yan, Xuewei Li, Wenjia Zhou, Wei Hong, Weitao Zheng, Feng Qi, Liming Peng   +6 more
semanticscholar   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

Hyperparameter Optimization and Feature Selection Analysis on the XGBoost Model for Hepatitis C Infection Prediction

Journal of Applied Informatics and Computing
Hepatitis C is a liver disease that can progress to chronic conditions such as cirrhosis and liver cancer. Early detection is essential and can be supported through machine learning approaches.
Nadia Martha Lefi, Majid Rahardi
doaj   +1 more source