Paper Info
Title
Ensemble adaptive network-based fuzzy inference system with weighted arithmetical mean and application to diagnosis of optic nerve disease from visual-evoked potential signals.
Abstract
This paper presents a new method based on combining principal component analysis (PCA) and adaptive network-based fuzzy inference system (ANFIS) to diagnose the optic nerve disease from visual-evoked potential (VEP) signals. The aim of this study is to improve the classification accuracy of ANFIS classifier on diagnosis of optic nerve disease from VEP signals. With this aim, a new classifier ensemble based on ANFIS and PCA is proposed.The VEP signals dataset include 61 healthy subjects and 68 patients suffered from optic nerve disease. First of all, the dimension of VEP signals dataset with 63 features has been reduced to 4 features using PCA. After applying PCA, ANFIS trained using three different training-testing datasets randomly with 50-50% training-testing partition.The obtained classification results from ANFIS trained separately with three different training-testing datasets are 96.87%, 98.43%, and 98.43%, respectively. And then the results of ANFIS trained with three different training-testing datasets randomly with 50-50% training-testing partition have been combined with three different ways including weighted arithmetical mean that proposed firstly by us, arithmetical mean, and geometrical mean. The classification results of ANFIS combined with three different ways are 98.43%, 100%, and 100%, respectively. Also, ensemble ANFIS has been compared with ANN ensemble. ANN ensemble obtained 98.43%, 100%, and 100% prediction accuracy with three different ways including arithmetical mean, geometrical mean and weighted arithmetical mean.These results have shown that the proposed classifier ensemble approach based on ANFIS trained with different train-test datasets and PCA has produced very promising results in the diagnosis of optic nerve disease from VEP signals.
Year
DOI
Venue
2008
10.1016/j.artmed.2008.03.007
Artificial Intelligence In Medicine
Keywords
Field
DocType
training-testing partition,vep signal,visual-evoked potential signals,ann ensemble,adaptive network-based fuzzy inference system,geometrical mean,classification result,different way,fuzzy inference system,ensemble anfis,ensemble adaptive,weighted arithmetical mean,anfis classifier,optic nerve disease,visual-evoked potential signal,principal component analysis,classifier ensemble,different training-testing datasets,arithmetic mean
Data mining,Computer science,Artificial intelligence,Adaptive neuro fuzzy inference system,Classifier (linguistics),Arithmetic function,Pattern recognition,Evoked potential,Geometric mean,Machine learning,Principal component analysis,Optic nerve,Fuzzy inference system
Journal
Volume
Issue
ISSN
43
2
0933-3657
Citations 
PageRank 
References 
10
0.81
10
Authors
5
Name
Order
Citations
PageRank
Bayram Akdemir1376.32
Sadik Kara227527.39
Kemal Polat3134897.38
Ayşegül Güven4869.08
Salih Güneş5126778.53