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Pregled bibliografske jedinice broj: 572371

Improvement of Hierarchical Clustering Results by Refinement of Variable Types and Distance Measures


Pinjušić Ćurić, Sofija; Vranić, Mihaela; Pintar, Damir
Improvement of Hierarchical Clustering Results by Refinement of Variable Types and Distance Measures // Automatika – Journal for Control, Measurement, Electronics, Computing and Communications, 52 (2011), 4; 353-364 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 572371 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Improvement of Hierarchical Clustering Results by Refinement of Variable Types and Distance Measures

Autori
Pinjušić Ćurić, Sofija ; Vranić, Mihaela ; Pintar, Damir

Izvornik
Automatika – Journal for Control, Measurement, Electronics, Computing and Communications (0005-1144) 52 (2011), 4; 353-364

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Hierarchical clustering; Distance measure; Variable types; Dendrogram

Sažetak
Hierarchical clustering method is used to assign observations into clusters further connected to form a hierarchical structure. Observations in the same cluster are close together according to the predetermined distance measure, while observations belonging to different clusters are afar. This paper presents an implementation of specific distance measure used to calculate distances between observations which are described by a mixture of variable types. Data mining tool ‘Orange’ was used for implementation, testing, data processing and result visualization. Finally, a comparison was made between results obtained by using already available widget and the output of newly programmed widget which employs new variable types and new distance measure. The comparison was made on different well-known datasets.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo



POVEZANOST RADA


Projekti:
036-0362027-1638 - Umrežena ekonomija (Skočir, Zoran, MZO ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Mihaela Vranić (autor)

Avatar Url Damir Pintar (autor)

Citiraj ovu publikaciju:

Pinjušić Ćurić, Sofija; Vranić, Mihaela; Pintar, Damir
Improvement of Hierarchical Clustering Results by Refinement of Variable Types and Distance Measures // Automatika – Journal for Control, Measurement, Electronics, Computing and Communications, 52 (2011), 4; 353-364 (međunarodna recenzija, članak, znanstveni)
Pinjušić Ćurić, S., Vranić, M. & Pintar, D. (2011) Improvement of Hierarchical Clustering Results by Refinement of Variable Types and Distance Measures. Automatika – Journal for Control, Measurement, Electronics, Computing and Communications, 52 (4), 353-364.
@article{article, author = {Pinju\v{s}i\'{c} \'{C}uri\'{c}, Sofija and Vrani\'{c}, Mihaela and Pintar, Damir}, year = {2011}, pages = {353-364}, keywords = {Hierarchical clustering, Distance measure, Variable types, Dendrogram}, journal = {Automatika – Journal for Control, Measurement, Electronics, Computing and Communications}, volume = {52}, number = {4}, issn = {0005-1144}, title = {Improvement of Hierarchical Clustering Results by Refinement of Variable Types and Distance Measures}, keyword = {Hierarchical clustering, Distance measure, Variable types, Dendrogram} }
@article{article, author = {Pinju\v{s}i\'{c} \'{C}uri\'{c}, Sofija and Vrani\'{c}, Mihaela and Pintar, Damir}, year = {2011}, pages = {353-364}, keywords = {Hierarchical clustering, Distance measure, Variable types, Dendrogram}, journal = {Automatika – Journal for Control, Measurement, Electronics, Computing and Communications}, volume = {52}, number = {4}, issn = {0005-1144}, title = {Improvement of Hierarchical Clustering Results by Refinement of Variable Types and Distance Measures}, keyword = {Hierarchical clustering, Distance measure, Variable types, Dendrogram} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Uključenost u ostale bibliografske baze podataka::


  • INSPEC
  • EBSCO





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