A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

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 ...

Abstract: Because of their transparency, interpretability, and efficiency in classification tasks, decision tree algorithms are the foundation of many Business Intelligence (BI) and Analytics ...

There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...

Mr. Currell was a deputy undersecretary and senior adviser at the Department of Education from 2018 to 2021. He is a trustee of Gustavus Adolphus College in St. Peter, Minn. This week, about 200,000 ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

Junior faculty are often told to protect their time, but nobody provides instructions for how to do so. As an assistant professor at a public university, I have struggled to balance my course load, my ...

Traditional classification techniques, such as Support Vector Machines (SVM), Decision Trees, and Naïve Bayes classifiers, have been widely used for both binary and multi-class problems (Opanasenko et ...

Recently, many machine learning techniques have been presented to detect brain lesions or determine brain lesion types using microwave data. However, there are limited studies analyzing the location ...