Abstract: Ordinal regression is a supervised learning problem where training samples are labeled by an ordinal scale. The ordering relation and nonmetric property of the label set distinguish it from ...

Consider a study of the effects on taste of various cheese additives. Researchers tested four cheese additives and obtained 52 response ratings for each additive. Each response was measured on a scale ...

This is a GitHub repository containing some deep learning models for ordinal regression (with pre-trained weights) in the PyTorch Hub / Torch Hub format. Note that this repository is not going to be a ...

ABSTRACT: There is a set of points in the plane whose elements correspond to the observations that are used to generate a simple least-squares regression line. Each value of the independent variable ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

Bitcoin Ordinals are a protocol introduced by Casey Rodarmor in January 2023, which enables data to be inscribed on Bitcoin’s blockchain by embedding content in transaction witnesses. This technology ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on this powerful machine learning technique used to predict a single numeric value. A regression problem is one ...

This research conducts a thorough reevaluation of seismic fragility curves by utilizing ordinal regression models, moving away from the commonly used log-normal distribution function known for its ...

The automatic prediction of the quality of a dialogue is useful to keep track of a spoken dialogue system’s performance and, if necessary, adapt its behavior. Classifiers and regression models have ...

The use of logistic regression models in data analysis and machine learning has expanded in recent years and has become the primary preference of researchers in risk assessment studies across a wide ...