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Polygonal data analysis: A new framework in symbolic data analysis
Knowledge-Based Systems, 2019Abstract This paper introduces a new framework for polygonal data analysis in the symbolic data analysis paradigm. We show that polygonal data generalizes bivariate interval data. A way for aggregating data in classes is presented to obtain symbolic datasets and, descriptive statistics (for instance, mean, variance, covariance, and histogram) and a ...
Wagner J.F. Silva +2 more
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International Journal of Signs and Semiotic Systems, 2014
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
Sandra Elizabeth González Císaro +1 more
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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
Sandra Elizabeth González Císaro +1 more
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Symbolic Objects and Symbolic Data Analysis
2005Today’s technology allows storing vast quantities of information from different sources in nature. This information has missing values, nulls, internal variation, taxonomies, and rules. We need a new type of data that allow us to represent the complexity of reality, maintaining the internal variation and structure (Bock & Diday, 2000; Diday, 2002 ...
Héctor Oscar Nigro +1 more
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Principal component analysis of interval data: a symbolic data analysis approach
Computational Statistics, 2000Statistical methods have been mainly developed for the analysis of single-valued variables. However, in real life there are many situations in which the use of these variables may cause severe loss of information. Dealing with quantitative variables, there are many cases in which a more complete information can be surely achieved by describing a set of
LAURO, NATALE, PALUMBO, FRANCESCO
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Data base for symbolic network analysis
IEE Proceedings G (Electronic Circuits and Systems), 1981A data base for generating the symbolic transfer functions for a linear electronic circuit is formulated and an appropriate retrieval theorem derived. The size of the required data base is 0 (n2) independently of the number of simultaneously varying parameters, where n is the total number of component output terminals, and the cost of retrieval is 0 ...
C.-C. Wu, R. Saeks
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Principles on Symbolic Data Analysis
2009Today’s technology allows storing vast quantities of information from different sources in nature. This information has missing values, nulls, internal variation, taxonomies, and rules. We need a new type of data analysis that allows us represent the complexity of reality, maintaining the internal variation and structure (Diday, 2003). In Data Analysis
Héctor Oscar Nigro +1 more
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Histograms in symbolic data analysis
Annals of Operations Research, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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R Symbolic Data Analysis for Symbolic Artificial Intelligence
Journal of Korean Institute of Intelligent Systems, 2017컴퓨터와 인간은 분명 다르지만 기본적으로 데이터를 저장하고 처리하는 개념적 측면에서는 서로 유사한 구조를 갖는다. 하지만 수집된 전체 데이터를 처리하고 분석하는 컴퓨터와는 달리 인간은 요약된 패턴 단위로 데이터를 처리한다. 즉 인간은 전체 데이터를 다루기보다는 요약된 정보를 통해 최적의 의사결정을 한다. 전체 데이터보다 요약된 정보만을 관리하면 시간과 비용 면에서 더 효율적인 시스템을 구축할 수 있다. 특히 빅데이터 환경에서 인공지능의 학습을 위한 대용량 데이터의 처리 및 분석을 위하여 요약된 정보에 기반 한 데이터학습에 대한 필요성이 제기되고 있다.
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Metrics in Symbolic Data Analysis
2005The Authors consider the general problem of similarity and dissimilarity measures in Symbolic Data Analysis. First they examine the classical definitions of elementary event, assertion object, hierarchical dependences and logical dependences, then they consider some well-known measures resemblance measures between two objects (Sokal-Michener, Roger ...
Luciano Nieddu, Alfredo Rizzi
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The Big Picture: Symbolic Data Analysis
CHANCE, 2013I went back to school this past spring semester. To be more precise, I sat in on a special topics course on symbolic data analysis offered by one of my colleagues who is a pioneer in this topic.
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