scholarly journals Mixture decomposition of distributions by copulas in the symbolic data analysis framework

2005 ◽  
Vol 147 (1) ◽  
pp. 27-41 ◽  
Author(s):  
E. Diday ◽  
M. Vrac
Keyword(s):  
Data Analysis ◽  
Analysis Framework ◽  
Symbolic Data Analysis ◽  
Symbolic Data ◽  
Mixture Decomposition ◽  
Decomposition Of Distributions

Symbolic Data Analysis

2014 ◽  
Vol 3 (1) ◽  
pp. 1-9
Author(s):  
Sandra Elizabeth González Císaro ◽  
Héctor Oscar Nigro
Keyword(s):  
Data Analysis ◽  
Complex Data ◽  
New Paradigm ◽  
Symbolic Data Analysis ◽  
Standard Data ◽  
Symbolic Data ◽  
The World ◽  
New Type ◽  
Mining Complex ◽  
Internal Variation

Standard data mining techniques no longer adequately represent the complexity of the world. So, a new paradigm is necessary. Symbolic Data Analysis is a new type of data analysis that allows us to represent the complexity of reality, maintaining the internal variation and structure developed by Diday (2003). This new paradigm is based on the concept of symbolic object, which is a mathematical model of a concept. In this article the authors are going to present the fundamentals of the symbolic data analysis paradigm and the symbolic object concept. Theoretical aspects and examples allow the authors to understand the SDA paradigm as a tool for mining complex data.

scholarly journals An introduction to symbolic data analysis and the SODAS software

2003 ◽  
Vol 7 (6) ◽  
pp. 583-601 ◽  
Author(s):  
Edwin Diday ◽  
Floriana Esposito
Keyword(s):  
Data Analysis ◽  
Symbolic Data Analysis ◽  
Symbolic Data
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