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Przegląd Statystyczny
|
2019
|
vol. 66
|
issue 1
84-93
EN
In the context of taxonomy methods in recent years, a lot of attention is paid to the stability of these methods, i.e. the answer to the question to what extent the structure discovered by a given method is actually present in the data? Many different ways of measuring stability have been proposed in the literature, which are mainly relating to the stability of the final grouping result. Lord et al. (2017) instead proposed a measure of stability for each observation from the data set and the measure of stability for individual groups. In their article, they suggest that an individual measure of stability may indicate noisy observation whereas the stability measure relating to particular groups may indicate clusters of noise which should be removed from the dataset. The aim of the paper is to apply the proposed individual measure of stability and a measure of stability for individual groups to answer the question to what extent Poland is matched the EU in terms of the level of sustainable development.
PL
We współczesnych rozważaniach z dziedziny taksonomii w literaturze często poruszane są dwa pojęcia: podejście zagregowane oraz stabilność metod grupowania. Do tej pory te były one rozważane osobno. Natomiast ciekawą propozycję w zakresie połączenia tych dwóch pojęć przedstawili Y. Șenbabaoğlu, G. Michailidis i J.Z. Li, którzy zasugerowali podejście zagregowane w taksonomii, połączone z zaproponowaną przez siebie miarą stabilności jako kryterium wyboru optymalnej liczby grup (k). Celem artykułu jest porównanie wyników wyboru wartości parametru k za pomocą wspomnianej miary stabilności oraz klasycznych indeksów (np. Calińskiego‑Harabasza, Dunna).
EN
Recently, the two concepts that have been often discussed in the literature on taxonomy are the cluster ensemble and stability. An interesting proposal regarding the combination of these two concepts was presented by Șenbabaoğlu, Michailidis, and Li, who proposed as a measure of stability a proportion of ambiguously clustered pairs (PAC) for selecting the optimal number of groups in the cluster ensemble. This proposal appeared in the field of genetic research, but as the authors themselves write, the method can be successfully used also in other research areas. The aim of this paper is to compare the results of indicating the number of clusters (k parameter) using the aggregated approach in taxonomy and the above-mentioned measure of stability and classical indices (e.g. Caliński–Harabasz, Dunn, Davies–Bouldin).
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