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Recursive Partition and Symbolic Data Analysis
1994The theory of symbolic objects is used to define a notion of data that generalizes the one typical of classical data analysis (data-as-matrices). The prediction problem for symbolic objects is defined: it is seen to be a generalization of the prediction problem for classical data. An algorithm of tree-growing is developed for symbolic objects.
A. Ciampi, E. Diday, J. Lebbe, R. Vignes
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Sensor Data Interpretation for Symbolic Analysis
2012This chapter describes an original contribute of this book: a method to solve the correspondence problem in multi-camera systems without the assumption of epipolar geometry. This method is suitable to reduce the sensory gap and the problem of the presence of mutual occlusions among moving objects inside a scene.
Alberto Amato +2 more
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Quality Issues in Symbolic Data Analysis
2007Symbolic Data Analysis is an extension of Classical Data Analysis to more complex data types and tables through the application of certain conditions, where underlying concepts are vital for their further processing. Therefore, the assessment of the quality of Symbolic Data depends extensively on the quality of the collected classical data.
Haralambos Papageorgiou, Maria Vardaki
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Symbolic Data Analysis Applied to Census Data
2008Use of symbolic data analysis to process Italian agricultural census ...
GIUSTI, ANTONIO, GRASSINI, LAURA
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Symbolic missing data imputation in principal component analysis
Statistical Analysis and Data Mining: The ASA Data Science Journal, 2011AbstractThe concept of symbolic data has been developed with the aim of representing variables whose measurement is affected by some internal variation. This idea has been mainly concerned with the need of aggregating individuals in order to summarize large datasets into smaller matrices of manageable size, retaining as much of the original knowledge ...
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Symbolic data analysis: what is it?
2007Classical data values are single points in p-dimensional space; symbolic data values are hypercubes (broadly defined) in p-dimensional space (and/or a cartesian product of p distributions). While some datasets, be they small or large in size, naturally consist of symbolic data, many symbolic datasets result from the aggregation of large or extremely ...
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An overview of real‐world data sources for oncology and considerations for research
Ca-A Cancer Journal for Clinicians, 2022Lynne Penberthy +2 more
exaly
Symbolic dynamics for medical data analysis
2002Observational data of natural systems, as measured in medical measurements are typically quite different from those obtained in laboratories. Due to the peculiarities of these data, wellknown characteristics, such as power spectra or fractal dimension, often do not provide a suitable description.
Wessel, Niels +3 more
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