Recently ordinal regression has attracted much interest in machine learning. The goal of ordinal regression is to assign each instance a rank, which should be as close as possible to its true rank. We propose an effective tree-based algorithm, called Ranking Tree, for ordinal regression. The main advantage of Ranking Tree is that it can group samples with closer ranks together in the process of...

The classical multivariate statistical method can only discuss the effectiveness of result, but can’t explain the cause and intrinsic mechanism when dealing with classification problems. In this paper, a new rough sets decision method based on the Principal Component Analysis (PCA) and the ordinal regression is proposed which may help to explain the cause and the intrinsic mechanism of classifi...

Many of the ordinal regression algorithms that have been proposed can be viewed as methods that minimize a convex surrogate of the zeroone, absolute, or squared errors. We provide a theoretical analysis of the risk consistency properties of a rich family of surrogate loss functions, including proportional odds and support vector ordinal regression. For all the surrogates considered, we either p...

This article examines empirically the factors determining the agro-industrial investments in Greece and their impact on tourism development. Firstly, the determinants influencing the spatial configuration, the socioeconomic forces and the political framework of the agro-industrial investments in Greece are examined theoretically, according to the literature considered by Regional Science. At ne...

We introduce a new methodology, called SVORIM+, for utilizing privileged information of the training examples, unavailable in the test regime, to improve generalization performance in ordinal regression. The privileged information is incorporated during the training by modelling the slacks through correcting functions for each of the parallel hyperplanes separating the ordered classes. The expe...

Automatic short answer grading (ASAG) can reduce tedium for instructors, but is complicated by free-form student inputs. An important ASAG task is to assign ordinal scores to student answers, given some “model” or ideal answers. Here we introduce a novel framework for ASAG by cascading three neural building blocks: Siamese bidirectional LSTMs applied to a model and a student answer, a novel poo...

Abstract: Quality evaluation and customer satisfaction measurement is a necessary condition for applying continuous improvement and total quality management philosophies. This justifies the need for developing modern operational research and management tools, which will be sufficient enough to analyse in detail customer satisfaction. The original applications presented through this paper implem...

Public bikesharing—the shared use of a bicycle fleet—has recently emerged in major North American cities. Bikesharing has been found to decrease driving and increase bicycling. But shifts in public transit have been mixed. The authors evaluate survey data from two U.S. cities to explore who is shifting toward and away from public transit as a result of bikesharing. The authors explore this ques...

Numerical precipitation prediction plays a crucial role in weather forecasting and has broad applications public services including aviation management urban disaster early-warning systems. However, numerical (NWP) models are often constrained by systematic bias due to coarse spatial resolution, lack of parameterizations, limitations observation conventional meteorological models, sample size l...