Multidimensional polarization for ordinal data

Multidimensional Interfaces for Selecting Data within Ordinal Ranges

Linked Data interfaces exist in many flavours, as evidenced by subject pages, sparql endpoints, triple pattern interfaces, and data dumps. These interfaces are mostly used to retrieve parts of a complete dataset, such parts can for example be defined by ranges in one or more dimensions. Filtering Linked Data by dimensions such as time range, geospatial area, or genomic location, requires the lo...

Modeling Paired Ordinal Response Data

 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...

Transition Models for Analyzing Longitudinal Data with Bivariate Mixed Ordinal and Nominal Responses

In many longitudinal studies, nominal and ordinal mixed bivariate responses are measured. In these studies, the aim is to investigate the effects of explanatory variables on these time-related responses. A regression analysis for these types of data must allow for the correlation among responses during the time. To analyze such ordinal-nominal responses, using a proposed weighting approach, an ...

Ordinal and Symbolic Data

Classification of Ordinal Data

Predictive learning has traditionally been a standard inductive learning, where different subproblem formulations have been identified. One of the most representative is classification, consisting on the estimation of a mapping from the feature space into a finite class space. Depending on the cardinality of the finite class space we are left with binary or multiclass classification problems. F...