Treffer: Saturated systems of homogeneous boxes and the logical analysis of numerical data
Title:
Saturated systems of homogeneous boxes and the logical analysis of numerical data
Authors:
Source:
Discrete Mathematics & Data Mining (DM & DM)Discrete applied mathematics. 144(1-2):103-109
Publisher Information:
Amsterdam; Lausanne; New York, NY: Elsevier, 2004.
Publication Year:
2004
Physical Description:
print, 7 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Logiciel, Software, Organisation des mémoires. Traitement des données, Memory organisation. Data processing, Traitement des données. Listes et chaînes de caractères, Data processing. List processing. Character string processing, Analyse numérique, Numerical analysis, Análisis numérico, Donnée binaire, Binary data, Dato binario, Informatique théorique, Computer theory, Informática teórica, Algorithme agglomération, Agglomeration algorithm, Algorithme amas, Cluster algorithm, Analyse donnée logique, Logical data analysis, Classification automatique boîte, Box clustering, Clustering
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
RUTCOR, Rutgers Center of Operations Research, Piscataway, NJ 08854, United States
School of Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ont, L1H 7K4, Canada
Department of Statistics, La Sapienza University, Piazzale Aldo Moro 5, 00185, Rome, Italy
Electronics and Computer Science, University of Southampton, United Kingdom
School of Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ont, L1H 7K4, Canada
Department of Statistics, La Sapienza University, Piazzale Aldo Moro 5, 00185, Rome, Italy
Electronics and Computer Science, University of Southampton, United Kingdom
ISSN:
0166-218X
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16182861
Database:
PASCAL Archive
Weitere Informationen
Following the general principles of the logical analysis of data methodology, originally developed for the case of binary data, we define a similar approach for the analysis of numerical data. The central concepts of this methodology are those of homogeneous boxes and of saturated systems of homogeneous boxes. The box-clustering heuristic described in this paper is efficient and was applied successfully for the analysis of datasets concerning breast tumors, oil exploration and diabetes.