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Categorical Data-Specifications
Theory and Applications of Categories, 1995 Summary: We introduce MD-sketches, which are a particular kind of Finite Sum sketches. Two interesting results about MD-sketches are proved. First, we show that, given two MD-sketches, it is algorithmically decidable whether their model categories are equivalent. Next we show that data-specifications as used in database-design and software engineering,
Piessens, Frank, Steegmans, Eric
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Slovenian Veterinary Research, 2023 Bluetongue (BT) is a non-contagious virus in the Reoviridae family that infects both wild and domestic animals. It causes economic losses and reduces infected animals' production and reproduction.
Iman E. El-Araby +3 more
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Outlier Analysis of Categorical Data using NAVF [PDF]
Informatică economică, 2013 Outlier mining is an important task to discover the data records which have an exceptional behavior comparing with other records in the remaining dataset. Outliers do not follow with other data objects in the dataset.
D. LAKSHMI SREENIVASA REDDY +2 more
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SIMPLE ALGORITHM TO CONSTRUCT CIRCULAR CONFIDENCE REGIONS IN CORRESPONDENCE ANALYSIS USING R
Barekeng, 2022 Correspondence analysis has been widely applied in various fields as a graphical method to depict the association structure between two categorical random variables on a low-dimensional plot. This study built a simple algorithm to determine the principal
Karunia Eka Lestari +2 more
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Clustering and variable selection for categorical multivariate data [PDF]
, 2013 This article investigates unsupervised classification techniques for categorical multivariate data. The study employs multivariate multinomial mixture modeling, which is a type of model particularly applicable to multilocus genotypic data.
Bontemps, Dominique, Toussile, Wilson
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Consumer Profile Identification and Allocation [PDF]
, 2007 We propose an easy-to-use methodology to allocate one of the groups which have been previously built from a complete learning data base, to new individuals. The learning data base contains continuous and categorical variables for each individual.
Cottrell, Marie +4 more
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Missing Categorical Data Imputation and Individual Observation Level Imputation
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2014 Traditional missing data techniques of imputation schemes focus on prediction of the missing value based on other observed values. In the case of continuous missing data the imputation of missing values often focuses on regression models.
Pavel Zimmermann +2 more
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Empirical analysis of rough set categorical clustering techniques based on rough purity and value set [PDF]
, 2017 Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, attention has been put on categorical data clustering, where data objects are made up of non-numerical attributes.
Abdulhasan, Raed abdulkareem +5 more
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Ignorability for categorical data
, 2005 We study the problem of ignorability in likelihood-based inference from incomplete categorical data. Two versions of the coarsened at random assumption (car) are distinguished, their compatibility with the parameter distinctness assumption is ...
Jaeger, Manfred
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Chain graph models of multivariate regression type for categorical data [PDF]
, 2011 We discuss a class of chain graph models for categorical variables defined by what we call a multivariate regression chain graph Markov property. First, the set of local independencies of these models is shown to be Markov equivalent to those of a chain ...
Lupparelli, Monia +1 more
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