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Statements

Subject Item
n2:RIV%2F00216224%3A14310%2F10%3A00045595%21RIV11-GA0-14310___
rdf:type
n10:Vysledek skos:Concept
dcterms:description
Introduction of a novel approach to the classification of vegetation data (species by plot matrices). This approach copes with a large amount of noise, groups irregularly shaped in attribute space and species turnover within groups. Method The proposed algorithm (Isopam) is based on the classification of ordination scores from isometric feature mapping. Ordination and classification are repeated in a search for either high overall fidelity of species to groups of sites, or high quantity and quality of indicator species for groups of sites. The classification is performed either as a hierarchical, divisive method or as non-hierarchical partitioning. In divisive clustering, resulting groups are subdivided until a stopping criterion is met. Isopam was tested on 20 real-world data sets. The resulting classifications were compared with solutions from eight widely used clustering algorithms. Introduction of a novel approach to the classification of vegetation data (species by plot matrices). This approach copes with a large amount of noise, groups irregularly shaped in attribute space and species turnover within groups. Method The proposed algorithm (Isopam) is based on the classification of ordination scores from isometric feature mapping. Ordination and classification are repeated in a search for either high overall fidelity of species to groups of sites, or high quantity and quality of indicator species for groups of sites. The classification is performed either as a hierarchical, divisive method or as non-hierarchical partitioning. In divisive clustering, resulting groups are subdivided until a stopping criterion is met. Isopam was tested on 20 real-world data sets. The resulting classifications were compared with solutions from eight widely used clustering algorithms.
dcterms:title
A brute-force approach to vegetation classification A brute-force approach to vegetation classification
skos:prefLabel
A brute-force approach to vegetation classification A brute-force approach to vegetation classification
skos:notation
RIV/00216224:14310/10:00045595!RIV11-GA0-14310___
n3:aktivita
n9:P n9:Z
n3:aktivity
P(GA206/09/0329), Z(MSM0021622416)
n3:cisloPeriodika
6
n3:dodaniDat
n11:2011
n3:domaciTvurceVysledku
n16:2938219
n3:druhVysledku
n5:J
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n12:predkladatel
n3:idSjednocenehoVysledku
244474
n3:idVysledku
RIV/00216224:14310/10:00045595
n3:jazykVysledku
n19:eng
n3:klicovaSlova
Cluster optimization; Indicator species; Isomap; Isometric feature mapping; Isopam; Twinspan; Vegetation databases
n3:klicoveSlovo
n13:Vegetation%20databases n13:Isomap n13:Isometric%20feature%20mapping n13:Isopam n13:Cluster%20optimization n13:Twinspan n13:Indicator%20species
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[79F084EDB4A4]
n3:nazevZdroje
Journal of Vegetation Science
n3:obor
n4:EF
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
4
n3:projekt
n18:GA206%2F09%2F0329
n3:rokUplatneniVysledku
n11:2010
n3:svazekPeriodika
21
n3:tvurceVysledku
Faude, Ulrike Feilhauer, Hannes Tichý, Lubomír Schmidtlein, Sebastian
n3:zamer
n6:MSM0021622416
s:issn
1100-9233
s:numberOfPages
10
n17:organizacniJednotka
14310