Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.

PURPOSERecent advances in machine learning have led to the development of classifiers that predict molecular subtypes of acute lymphoblastic leukemia (ALL) using RNA-sequencing (RNA-seq) data.

This paper presents a comprehensive machine learning approach for credit score classification, addressing key challenges in financial risk assessment. We propose an optimized CatBoost-based framework ...

This section elaborates on the classification performance of the three machine learning models—Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)—for predicting coronary ...

A Class 3A public school that faced promotion to 4A for the initial classification system reasonably could contend that it shouldn’t be moved up based on its state tournament performance as it ...

In machine learning, multi-task learning (MTL) has emerged as a powerful paradigm that enables concurrent training of multiple interrelated algorithms. By exploiting the inherent connections between ...