The problem of ordinal regression, in which the goal is to learn a rule to predict labels from a discrete but ordered set, has gained considerable attention in machine learning in recent years. We study generalization properties of algorithms for this problem. We start with the most basic algorithms that work by learning a real-valued function in a regression framework and then rounding off a p...

Beef cattle research commonly uses Yield grade (YG) and Quality grade (QG) as outcomes in nutrition and health experiments. These outcomes, as commonly reported and analyzed, are ordinal variables with an assumed rank derived from an underlying latent variable that may or may not be available for analysis. The objective of this study was to employ mixed-effects ordinal regression and approaches...

 About 25 years ago, McCullagh proposed a method for modeling univariate ordinal responses. After publishing this paper, other statisticians gradually extended his method, such that we are now able to use more complicated but efficient methods to analyze correlated multivariate ordinal data, and model the relationship between these responses and host of covariates. In this paper, we aim to...

The purpose of this study was to examine the rate at which lesbian, gay, and bisexual United States citizens are victims of physical assaults due to their sexual orientation. The research consisted of 198 participants. Closed ended surveys were provided to the participants. The question for this study was “How many times have you been physically assaulted because of your sexual orientation”. An...

Supervised learning is characterized by a broad spectrum of learning problems, often involving structured types of prediction, including classification, ranking-based predictions (label and instance ranking), and (ordinal) regression in its various forms. All these different learning problems are typically addressed by specific algorithmic solutions. In this chapter, we propose a general prefer...

Community-based systems of care (SOC) provide a range of services to students with significant emotional and behavioral difficulties and their families. However, little is known about the educational characteristics and functioning of students at enrollment in SOC. The purpose of this study was to replicate and extend previous research by examining the educational characteristics and predictors...

Supervised learning is characterized by a broad spectrum of learning problems, often involving structured predictions, including classification and regressions problems, ranking-based predictions (label and instance ranking), and ordinal regression in its various forms. All these different learning problems are typically addressed by specific algorithmic solutions. In this paper, we show that t...