Results 101 to 110 of about 95,729 (269)
Transportation and Information Technologies in RussiaBackground. Accurate forecasting of the energy consumption of electric vehicles is a critically important task for improving the efficiency of vehicle operation and reducing drivers' anxiety about power reserve.
Vladislav V. Matviyuk
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng +4 more
wiley +1 more source
Cyprus Journal of Medical SciencesBACKGROUND/AIMS: Diabetes is one of the paramount public health challenges, affecting millions worldwide. Classification models can boost early detection and aid in treatment, particularly for diabetes type 2.
Bardia Arman +4 more
doaj +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 +3 more
core
Breast Cancer Classification using XGBoost
World Journal of Advanced Research and ReviewsBreast cancer continues to be one of the foremost illnesses that results in the deaths of numerous women each year. Among the female population, approximately 8% are diagnosed with Breast cancer (BC), following Lung Cancer. The alarming rise in fatality rates can be attributed to breast cancer being the second leading cause.
Rahmanul Hoque +3 more
openaire +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
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 +2 more
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Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Leveraging Machine Learning to Predict Academic Specialization Pathways in Higher Education
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)This study developed a machine learning-based model to predict academic concentration selection among information systems students at Universitas Multimedia Nusantara (UMN).
Rendy Wirawan Tamrin, Wella
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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