Back to Search
Start Over
A hybrid algorithm of interval type-2 fuzzy logic system and generalized adaptive resonance theory for medical data classification.
- Source :
- Intelligent Decision Technologies; 2019, Vol. 13 Issue 1, p81-89, 9p
- Publication Year :
- 2019
-
Abstract
- The hybrid of artificial neural network (ANN) and fuzzy logic system (FLS) can expend itself dynamically in a strong discovery of explicit knowledge to solve classification and regression problems with new input patterns. In this paper, a hybrid of Generalized Adaptive Resonance Theory (GART) and interval type-2 fuzzy logic system (IT2FLS) algorithm is proposed, and named as Generalized Adaptive Resonance Theory and interval type-2 fuzzy logic system (GART-IT2FLS). The GART is a combination of adaptive resonance theory network (ART) and Generalized Regression Neural Network (GRNN). GART is capable to deal with classification task effectively. However, type-2 fuzzy sets (T2 FS) is used to represent and model the uncertainties on inputs. The performance evaluation of GART-IT2FLS algorithm in three medical datasets has proven that GART-IT2FLS is capable to learn incrementally without plasticity-stability dilemma, and model uncertainties in medical datasets. The inferences of GAR-IT2FLS in these applications are discussed. The performance results show that GART-IT2FLS has obtained a comparable number of rules. The Wisconsin Breast Cancer and Heart Disease experiments demonstrated GART-IT2FLS has improved the testing accuracies. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18724981
- Volume :
- 13
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Intelligent Decision Technologies
- Publication Type :
- Academic Journal
- Accession number :
- 135825507
- Full Text :
- https://doi.org/10.3233/IDT-190358