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Proximity measures in symbolic data analysis
Statistica, 2007 The Authors consider the general problem of similarity and dissimilarity measures in Symbolic Data Analysis. First of all they examine the classical definitions of elementary event, assertion object, hierarchical dependences and logical dependences. Then
Luciano Nieddu, Alfredo Rizzi
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The climatic factors affecting dengue fever outbreaks in southern Taiwan: an application of symbolic data analysis [PDF]
BioMedical Engineering OnLine, 2018 Background Dengue fever is a leading cause of severe illness and hospitalization in Taiwan. This study sought to elucidate the linkage between dengue fever incidence and climate factors. Results The result indicated that temperature, accumulated rainfall,
Yi-Horng Lai
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New models for symbolic data analysis [PDF]
Advances in Data Analysis and Classification, 2022 AbstractSymbolic data analysis (SDA) is an emerging area of statistics concerned with understanding and modelling data that takes distributional form (i.e. symbols), such as random lists, intervals and histograms. It was developed under the premise that the statistical unit of interest is the symbol, and that inference is required at this level.
Boris Beranger, Huan Lin, Scott Sisson
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Symbolic Analysis for Data Plane Programs Specialization [PDF]
ACM Transactions on Architecture and Code Optimization, 2022 Programmable network data planes have extended the capabilities of packet processing in network devices by allowing custom processing pipelines and agnostic packet processing. While a variety of applications can be implemented on current programmable data planes, there are significant constraints due to hardware limitations.
Thomas Luinaud +2 more
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An Introduction to Symbolic data Analysis and its Application to the Sodas Project
Revista de Matemática: Teoría y Aplicaciones, 2012 Las descripciones de los datos de las unidades se llaman "simbólicas" cuando son más complejas que las estándar debido al hecho que contienen variación interna y están estructuradas. Los datos simbólicos aparecen a través de diversas fuentes, por ejemplo
Edwin Diday
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Extracting Information from Interval Data Using Symbolic Principal Component Analysis
Austrian Journal of Statistics, 2017 We introduce generic definitions of symbolic variance and covariance for random interval-valued variables, that lead to a unified and insightful interpretation of four known symbolic principal component estimation methods: CPCA, VPCA, CIPCA, and ...
M. R. Oliveira +4 more
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An Introduction to symbolic data analysis
, 1993 The main aim of the symbolic approach in data analysis is to extend problems, methods and algorithms used on standard data to more complex data called "symbolic objects" in order to distinguish them from objects (described by numerical or categorical variables) treated by standard data nalysis methods.
Edwin Diday
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Symbolic Data Analysis and Formal Concept Analysis
, 2011 L'analyse formelle de concepts (FCA) est utilisée pour construire des treillis de concepts à partir de tables de données binaires pour des besoins de découverte de connaissances. Les structures de patrons en FCA sont capables de prendre en compte des données complexes et de plus fournissent une vue concise et algorithmique efficace sur le formalisme ...
Kaytoue, Mehdi +3 more
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