An artificial intelligence-driven model developed by Halima Haque, graduate student at Independent University, Bangladesh, ...

GDP prediction is a complex task, influenced by multiple economic factors such as government expenditure, foreign direct investment (FDI), remittance inflows, inflation, and official development aid.

Feature selection is a critical process in ML that helps eliminate irrelevant or redundant variables, leading to better generalization and model efficiency. The study proposes a Hybrid Feature ...

Discover how AI and DNA methylation revolutionize brain tumor diagnosis, increasing accuracy, and identifying new therapeutic ...

Abstract: This study presents a novel multi-model fusion approach for enhancing land surface temperature (LST) recovery and spatial resolution improvement. We compare and integrate linear Ridge ...

Researchers employed advanced deep learning models, such as Random Forest (RF), Decision Trees (DT), and K-Nearest Neighbor (KNN), to assess and anticipate changes in player movements with an ...

Image Credit: Edward Haylan / Shutterstock Advanced AI models for coral health predictions ... support vector machines (SVM), and random forests (RF) to analyze vast amounts of reef data, allowing ...

To address these challenges, this study proposes a novel Integrated Multi-Algorithm Feature Optimization Model (IMAFOM) that combines three filtering algorithms with a random forest (RF) algorithm for ...

This repository contains a regression-based variant of the original model developed by Jonathan Brophy and Daniel Lowd as described in Machine Unlearning for Random Forests. The main objective of this ...

A total of 26 ML models were included, and the AUCs of models that were used three or more times were pooled. Among them, the random forest (RF) models demonstrated the best performance with a pooled ...