Categorical data appears in various places, and dealing with it has been a major concern in analysis fields. However, representing not only global trends but also local trends of d...
Background: Genomics and proteomics analyses regularly involve the simultaneous test of hundreds of hypotheses, either on numerical or categorical data. To correct for the occurre...
Anyela Camargo, Francisco Azuaje, Haiying Wang, Hu...
Simple presentation graphics are intuitive and easy-to-use, but only show highly aggregated data. Bar charts, for example, only show a rather small number of data values and x-y-pl...
The grade of membership (GoM) model uses fuzzy sets as memberships of each individual to extreme profiles (or classes) on the likelihood function of multivariate multinomial distr...
The textile plot is a parallel coordinate plot in which the ordering, locations and scales of the axes are simultaneously chosen so that the connecting lines, each of which repres...
We propose a model for a point-referenced spatially correlated ordered categorical response and methodology for estimation of model parameters. Models and methods for spatially co...
Abstract. Frequent itemsets and association rules are generally accepted concepts in analyzing item-based databases. The Apriori-framework was developed for analyzing categorical d...
Measuring similarity or distance between two entities is a key step for several data mining and knowledge discovery tasks. The notion of similarity for continuous data is relative...
This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is th...
Abstract. Nonparametric predictive inference (NPI) is a powerful frequentist statistical framework based only on an exchangeability assumption for future and past observations, mad...
Frank P. A. Coolen, Pauline Coolen-Schrijner, Taha...