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Data reduction models for interval valued observations

Authors: COPPI R; D'URSO, Pierpaolo; GIORDANI, Paolo;

Data reduction models for interval valued observations

Abstract

La complessità dei fenomeni reali spesso richiede la trattazione di dati che non si presentano come singoli valori numerici ma in forme più complesse, ad esempio in forma di intervallo. Anche in queste situazioni, può rendersi utile sintetizzare i dati a disposizione, riducendo al minimo la perdita di informazione. L’Analisi in Componenti Principali è una nota tecnica che raggiunge tale obiettivo in presenza di dati numerici. In questo lavoro, viene proposta una estensione di tale tecnica alla trattazione di dati intervallari. Il modello in questione determina le componenti principali sfruttando l’informazione fornita non solo dal punto centrale degli intervalli (midpoint) ma anche da una misura della loro ampiezza (radius).

Country
Italy
Related Organizations
Keywords

principal component analysis; interval valued data

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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