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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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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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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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Consequences of Categorical Labeling of Preschool Children [PDF]
, 1988 The use of categorical diagnostic labels prescribed in P.L. 94--142 with children below school age is examined in this article. National practices relative to categorical labeling are reviewed, and questions are posed concerning the consequences of ...
Kerns, Georgia M., Mallory, Bruce L.
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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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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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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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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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Tree-Based Contrast Subspace Mining for Categorical Data
International Journal of Computational Intelligence Systems, 2020 Mining contrast subspace has emerged to find subspaces where a particular queried object is most similar to the target class against the non-target class in a two-class data set.
Florence Sia, Rayner Alfred, Yuto Lim
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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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