Results 61 to 70 of about 1,816,247 (166)
Assessing Measurement Equivalence in Ordered-Categorical Data
Psicológica, 2012 La invarianza factorial estudia de la equivalencia métrica en el marco del modelo lineal del factor común por medio de la comparación de los parámetros del modelo de medida en los grupos de interés.
Paula Elosua
doaj
A Multivariate Fuzzy Weighted K-Modes Algorithm with Probabilistic Distance for Categorical Data
Journal of ICT Research and ApplicationsData clustering is a data mining approach that assigns similar data to the same group. Traditionally, cluster similarity considers all attributes equally, but in real-world applications, some attributes may be more important than others. Therefore, this
Ren-Jieh Kuo +3 more
doaj +1 more source
Clustering categorical data streams
Journal of Computational Methods in Sciences and Engineering, 2011 In this paper, we propose an efficient clustering algorithm for analyzing categorical data streams. It has been proved that the proposed algorithm uses small memory footprints. We provide empirical analysis on the performance of the algorithm in clustering both synthetic and real data streams.
He, Zengyou +3 more
openaire +2 more sources
Assessing Measurement Equivalence in Ordered-Categorical Data
Psicológica, 2011 La invarianza factorial estudia de la equivalencia métrica en el marco del modelo lineal del factor común por medio de la comparación de los parámetros del modelo de medida en los grupos de interés.
Paula Elosua
doaj
Analyzing Biomedical Datasets with Symbolic Tree Adaptive Resonance Theory
InformationBiomedical datasets distill many mechanisms of human diseases, linking diseases to genes and phenotypes (signs and symptoms of disease), genetic mutations to altered protein structures, and altered proteins to changes in molecular functions and ...
Sasha Petrenko +7 more
doaj +1 more source
Application of Genetic Algorithm Based Intuitionistic Fuzzy k-Mode for Clustering Categorical Data
Cybernetics and Information Technologies, 2017 In present times a great number of clustering algorithms are available which group objects having similar features. But most of the datasets have data values that are categorical, which makes it difficult to implement these algorithms.
Goyal Akarsh +2 more
doaj +1 more source
Comparison of methods in the analysis of dependent ordered catagorical data [PDF]
Rating scales for outcome variables produce categorical data which are often ordered and measurements from rating scales are not standardized. The purpose of this study is to apply commonly used and novel methods for paired ordered categorical data to ...
Högberg, Hans, Svensson, Elisabeth
core
Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data. [PDF]
J Mach Learn Res, 2023 Gu Y, Erosheva EA, Xu G, Dunson DB.
europepmc +1 more source
Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation. [PDF]
Adv Neural Inf Process Syst, 2022 Ni Y.
europepmc +1 more source