Ordinal regression and classification methods form a vital branch of statistical learning wherein the outcome variable possesses an inherent order. Unlike conventional classification problems, where ...

Abstract: Ordinal regression is commonly formulated as a multiclass problem with ordinal constraints. The challenge of designing accurate classifiers for ordinal regression generally increases with ...

This repository contains data and an R markdown document walking through an example of ordinal regression in brms. The data is from a study by Michael Correll and colleagues' CHI 2020 paper, ...

Abstract: Like many psychological scales, depression scales are ordinal in nature. Depression prediction from behavioral signals has so far been posed either as classification or regression problems.

Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich domains, ...

1 Department of Applied Ecology, Center for Marine Sciences and Technology, North Carolina State University, Morehead City, NC, United States 2 College of Marine Sciences, Shanghai Ocean University, ...

1 Department of Mobility and Infrastructure Planning and Management, College of Urban Development and Engineering, Ethiopian Civil Service University, Addis Ababa, Ethiopia 2 Faculty of Civil ...