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» A Novel Distance Measure for Interval Data
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PRIS
2007
13 years 6 months ago
A Novel Distance Measure for Interval Data
Interval data is attracting attention from the data analysis community due to its ability to describe complex concepts. Since clustering is an important data analysis tool, extendi...
Jie Ouyang, Ishwar K. Sethi
ESANN
2007
13 years 6 months ago
Interval discriminant analysis using support vector machines
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
Cecilio Angulo, Davide Anguita, Luis Gonzál...
PRL
2006
139views more  PRL 2006»
13 years 4 months ago
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...
ESWA
2010
158views more  ESWA 2010»
13 years 2 months ago
Interval competitive agglomeration clustering algorithm
1 In this study, a novel robust clustering algorithm, robust interval competitive agglomeration (RICA) clustering algorithm, is proposed to overcome the problems of the outliers, t...
Jin-Tsong Jeng, Chen-Chia Chuang, Chin-Wang Tao
ORL
2008
99views more  ORL 2008»
13 years 4 months ago
Some tractable instances of interval data minmax regret problems
This paper focuses on tractable instances of interval data minmax regret graph problems. More precisely, we provide polynomial and pseudopolynomial algorithms for sets of particul...
Bruno Escoffier, Jérôme Monnot, Olivi...