- Tytuł:
-
Porównanie stabilności zagregowanych algorytmów taksonomicznych opartych na idei metody bagging
Comparison of Stability of Cluster Ensembles based on Bagging Idea - Autorzy:
- Rozmus, Dorota
- Powiązania:
- https://bibliotekanauki.pl/articles/587052.pdf
- Data publikacji:
- 2013
- Wydawca:
- Uniwersytet Ekonomiczny w Katowicach
- Tematy:
-
Agregacja modeli
Algorytmy
Metody taksonomiczne
Aggregation models
Algorithms
Taxonomic methods - Opis:
- Ensemble approach has been successfully applied in the context of supervised learning to increase the accuracy and stability of classification. One of the most popular method is bagging based on bootstrap samples. Recently, analogous techniques for cluster analysis have been suggested in order to increase classification accuracy, robustness and stability of the clustering solutions. Research has proved that, by combining a collection of different clusterings, an improved solution can be obtained. A desirable quality of the method is the stability of a clustering algorithm with respect to small perturbations of data (e.g., data subsampling or resampling, small variations in the feature values) or the parameters of the algorithm (e.g., random initialization). Here, we look at the stability of the ensemble and carry out an experimental study to compare stability of cluster ensembles based on bagging idea.
- Źródło:
-
Studia Ekonomiczne; 2013, 133; 119-134
2083-8611 - Pojawia się w:
- Studia Ekonomiczne
- Dostawca treści:
- Biblioteka Nauki
Artykuł