The goal of the proposed work is improving prediction accuracy in drift detection using Logistic Regression compared with modified light gradient boost model. The collection of 40 samples were taken ...

Sahin, E.K. (2020) Assessing the Predictive Capability of Ensemble Tree Methods for Landslide Susceptibility Mapping Using XGBoost, Gradient Boosting Machine, and Random Forest. SN Applied Sciences, 2 ...

Low-light image enhancement is of interest in many practical applications, such as low-light photography and video surveillance. Traditional methods, like histogram equalization-based methods, cannot ...

Using various machine learning models (Logistic Regression, Gaussian Naïve Bayes, KNN, Gradient Boosting Classifier, Decision Tree Classifier, Random Forest Classifier.) to predict whether a company ...

Objectives: the purpose of this research was to create and validate radiomic models based on machine learning that can effectively discriminate between primary non-small cell lung cancer (NSCLC) and ...

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