- Tytuł:
- Application of modified fuzzy clustering to medical data classification
- Autorzy:
- Jeżewski, M.
- Powiązania:
- https://bibliotekanauki.pl/articles/333509.pdf
- Data publikacji:
- 2011
- Wydawca:
- Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
- Tematy:
-
grupowanie rozmyte
klasyfikacja
dane medyczne
fuzzy clustering
classification
medical data - Opis:
- Classification plays very important role in medical diagnosis. This paper presents fuzzy clustering method dedicated to classification algorithms. It focuses on two additional sub-methods modifying obtained clustering prototypes and leading to final prototypes, which are used for creating the classifier fuzzy if-then rules. The main goal of that work was to examine a performance of the classifier which uses such rules. Commonly used including medical benchmark databases were applied. In order to validate the results, each database was represented by 100 pairs of learning and testing subsets. The obtained classification quality was better in relation to the one of the best classifiers - Lagrangian SVM and suggests that presented clustering with additional sub-methods are appropriate to application to classification algorithms.
- Źródło:
-
Journal of Medical Informatics & Technologies; 2011, 17; 51-57
1642-6037 - Pojawia się w:
- Journal of Medical Informatics & Technologies
- Dostawca treści:
- Biblioteka Nauki
Artykuł