- Tytuł:
- Neuro-rough-fuzzy approach for regression modelling from missing data
- Autorzy:
- Simiński, K.
- Powiązania:
- https://bibliotekanauki.pl/articles/331298.pdf
- Data publikacji:
- 2012
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
system neuronowo-rozmyty
ANNBFIS
brakujące wartości
zbiór przybliżony
zbiór rozmyty
neuro-fuzzy
missing values
marginalisation
imputation
rough fuzzy set
clustering - Opis:
- Real life data sets often suffer from missing data. The neuro-rough-fuzzy systems proposed hitherto often cannot handle such situations. The paper presents a neuro-fuzzy system for data sets with missing values. The proposed solution is a complete neuro-fuzzy system. The system creates a rough fuzzy model from presented data (both full and with missing values) and is able to elaborate the answer for full and missing data examples. The paper also describes the dedicated clustering algorithm. The paper is accompanied by results of numerical experiments.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2012, 22, 2; 461-476
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł