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  • Search: subject:"AHCA (agglomerative hierarchical clustering algorithm)"
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Year of publication
Subject
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AHCA (agglomerative hierarchical clustering algorithm) 4 admissibility 4 monotonicity 2 space distortion 2 structure 2
Online availability
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Free 4
Type of publication
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Book / Working Paper 4
Type of publication (narrower categories)
All
Working Paper 2
Language
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English 2 Undetermined 2
Author
All
Inada, Koichi 4 Takeuchi, Akinobu 4 Yadohisa, Hiroshi 4
Institution
All
Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät 2
Published in...
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SFB 373 Discussion Paper 2 SFB 373 Discussion Papers 2
Source
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EconStor 2 RePEc 2
Showing 1 - 4 of 4
Cover Image
Space distortion and monotone admissibility in agglomerative clustering
Takeuchi, Akinobu; Yadohisa, Hiroshi; Inada, Koichi - 2001
This paper discusses the admissibility of agglomerative hierarchical clustering algorithms with respect to space distortion and monotonicity, as defined by Yadohisa et al. and Batagelj, respectively. Several admissibilities and their properties are given for selecting a clustering algorithm....
Persistent link: https://www.econbiz.de/10010310326
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Cover Image
Measures for the structure of clustering and admissibilities of its algorithm
Takeuchi, Akinobu; Yadohisa, Hiroshi; Inada, Koichi - 2001
The problem of selecting a clustering algorithm from the myriad of algorithms has been discussed in recent years. Many researchers have attacked this problem by using the concept of admissibility (e.g. Fisher and Van Ness, 1971, Yadohisa, et al., 1999). We propose a new criterion called the...
Persistent link: https://www.econbiz.de/10010310420
Saved in:
Cover Image
Space distortion and monotone admissibility in agglomerative clustering
Takeuchi, Akinobu; Yadohisa, Hiroshi; Inada, Koichi - Sonderforschungsbereich 373, Quantifikation und … - 2001
This paper discusses the admissibility of agglomerative hierarchical clustering algorithms with respect to space distortion and monotonicity, as defined by Yadohisa et al. and Batagelj, respectively. Several admissibilities and their properties are given for selecting a clustering algorithm....
Persistent link: https://www.econbiz.de/10010956414
Saved in:
Cover Image
Measures for the structure of clustering and admissibilities of its algorithm
Takeuchi, Akinobu; Yadohisa, Hiroshi; Inada, Koichi - Sonderforschungsbereich 373, Quantifikation und … - 2001
The problem of selecting a clustering algorithm from the myriad of algorithms has been discussed in recent years. Many researchers have attacked this problem by using the concept of admissibility (e.g. Fisher and Van Ness, 1971, Yadohisa, et al., 1999). We propose a new criterion called the...
Persistent link: https://www.econbiz.de/10010956549
Saved in:
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