- Tytuł:
- An ε-Insensitive Approach to Fuzzy Clustering
- Autorzy:
- Łęski, J.
- Powiązania:
- https://bibliotekanauki.pl/articles/908067.pdf
- Data publikacji:
- 2001
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
programowanie
metoda grupowania
fuzzy clustering
fuzzy c-means
robust methods
varepsilon-insensitivity
fuzzy c-medians - Opis:
- Fuzzy clustering can be helpful in finding natural vague boundaries in data. The fuzzy c-means method is one of the most popular clustering methods based on minimization of a criterion function. However, one of the greatest disadvantages of this method is its sensitivity to the presence of noise and outliers in the data. The present paper introduces a new varepsilon-insensitive Fuzzy C-Means (varepsilonFCM) clustering algorithm. As a special case, this algorithm includes the well-known Fuzzy C-Medians method (FCMED). The performance of the new clustering algorithm is experimentally compared with the Fuzzy C-Means (FCM) method using synthetic data with outliers and heavy-tailed, overlapped groups of the data.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2001, 11, 4; 993-1007
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł