The eXtreme Gradient Boosting (XGBoost) algorithm demonstrates remarkable ... SmoteR, an adaptation of the original SMOTE algorithm originally developed for classification tasks, is specifically ...

The final classification of a data point is based on the simple majority voting scheme. + Resilient to overfitting. Boosting algorithms (XGBoost, Adaboost ... rule‐based methods for certain linguistic ...

SVM demonstrates proficiency in the classification of small, high-dimensional datasets, while DT algorithms, particularly ensemble methods such as RF and XGBoost, exhibit efficacy ... maps local to ...

By combining machine learning-based text classification and sentiment analysis, we can create a robust AI-powered email ...

IT white papers, webcasts, case studies, and much more - all free to registered TechRepublic members. These guidelines ensure IT workers keep up to date with the latest technology trends and ...

This compares ML models, such as Random Forest (RF) and XGBoost, against deep learning models, such as Long Short-Term Memory (LSTM), in terms of the accuracy of their market forecasting over ...

We consider the UC Irvin knowledge discovery dataset. So, this paper proposes the XGBoost algorithm to predict thyroid disease accurately. The best features are selected using XGBoost function. The ...

To address this challenge, we propose a Blockchain-Based Collaborative Task Offloading Algorithm in Heterogeneous Edge Computing Networks (BCTOH). By introducing blockchain technology, the algorithm ...