IEEE

Gradient Boosting-Based Simultaneous Classification and Regression Approach

Abstract: The recent development of advanced data analytics and machine learning promoted the introduction of diverse learning techniques designed to alleviate challenges related to two major ...
Scientific Research Publishing

Utubor, S. (2023) Improving Detection of Attacks in Cyber-Physical Systems: Applying Gradient Boosting Based Machine Learning Techniques. Ph.D. Thesis, The George Washington ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
Frontiers

The diagnostic value of convolutional neural networks in thyroid cancer detection using ultrasound images

Objective: To extract and analyze the image features of two-dimensional ultrasound images and elastic images of four thyroid nodules by radiomics, and then further convolution processing to construct ...
Frontiers

Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transfer

1 Guangxi Reproductive Medical Center, The First Affiliated Hospital of Guangxi Medical University, Nanning, China 2 Reproductive Center, Nanning Maternity and Child Health Hospital, Nanning, Guangxi, ...
IEEE

Gradient Boosting Feature Selection For Integrated Fault Diagnosis in Series-Compensated Transmission Lines

Abstract: Series-compensated power transmission lines are integral to modern power grids and enhance system reliability and stability. However, they introduce challenges such as voltage inversion, ...
C&EN

Optimized Gradient Boosting Models for Adaptive Prediction of Uniaxial Compressive Strength in Carbonate Rocks Using Drilling Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...
Scientific Research Publishing

Kalusivalingam, A.K., Sharma, A., Patel, N. and Singh, V. (2022) Leveraging Random Forests and Gradient Boosting for Enhanced Predictive Analytics in Operational Efficiency ...

ABSTRACT: Accurate prediction of treatment response in bipolar disorder patients with comorbid obsessive-compulsive disorder (OCD) is essential to improving clinical outcomes and minimizing ...
C&EN

XGBMUT: Predicting the Functional Impact of Missense Mutations Using an Extreme Gradient Boost Classifier

Laboratory of Molecular Modeling and QSAR, Faculty of Pharmacy, Federal University of Rio de Janeiro, 373 Carlos Chagas Filho Avenue, Rio de Janeiro, Rio de Janeiro 21941-170, Brazil Laboratory of ...