Researchers from the Data Science and Artificial Intelligence Institute (DATAI) of the University of Navarra (Spain) have ...

Finally, we discuss how alternatives such as random ferns and extremely randomized trees stem from our more general forest model. This document is directed at both students who wish to learn the ...

Consequently, in this article, a novel decision-making method designed to meet the demands of multiple reactive tasks is proposed to serve autonomous driving sweepers. Smart nodes (smart sequence and ...

Abstract: Gradient-boosting decision tree classifiers (GBDTs ... perturbation attacks using symmetric adversarial samples in order to obtain correct classification. We apply and evaluate the symmetry ...

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning ...

Prognostic and clinical decision making theory are explored in consideration ... Class contact times vary by course and type of module. Typically, for a module predominantly delivered through lectures ...

Various classification algorithms, including Random Forest, Logistic Regression, Decision Tree, and K-Nearest Neighbors (KNN), were trained to classify accident types. The primary goal of this project ...

Introduction: Maternal health is a critical aspect of public health that affects the wellbeing of both mothers and infants. Despite medical advancements, maternal mortality rates remain high, ...

Retinal blood vessel morphological abnormalities are generally associated with cardiovascular, cerebrovascular, and systemic diseases, automatic artery/vein (A/V) classification is particularly ...