scholarly journals A Neuro-Fuzzy Modeling using the Hierarchical Clustering and Gaussian Mixture Model

2003 ◽  
Vol 13 (5) ◽  
pp. 512-519 ◽  
Author(s):  
Sung-Suk Kim ◽  
Keun-Chang Kwak ◽  
Jeong-Woong Ryu ◽  
Myung-Geun Chun
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Hierarchical Clustering ◽  
Gaussian Mixture ◽  
Fuzzy Modeling ◽  
Neuro Fuzzy

scholarly journals A Neuro-Fuzzy System Modeling using Gaussian Mixture Model and Clustering Method

2002 ◽  
Vol 12 (6) ◽  
pp. 571-576
Author(s):  
Sung-Suk Kim ◽  
Keun-Chang Kwak ◽  
Jeong-Woong Ryu ◽  
Myung-Geun Chun
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Fuzzy System ◽  
System Modeling ◽  
Gaussian Mixture ◽  
Clustering Method ◽  
Neuro Fuzzy

scholarly journals Gaussian Mixture Model Based Hierarchical Clustering in Prediction of Autism Spectrum Disorder

2019 ◽  
Vol 8 (3) ◽  
pp. 5751-5756
Keyword(s):  
Autism Spectrum Disorder ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Hierarchical Clustering ◽  
Classification Accuracy ◽  
Gaussian Mixture ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Model Based ◽  
Proper Diagnosis

Autism is one of the most complex and divergent class disorders which accompany various lacking in symptoms needed for classification, societal interaction, abridged verbal communication, and monotonous behavior. Timely and proper diagnosis of Autism Spectrum Disorder can ensure the offering of medical treatment and guidance to get cure. In this paper, Gaussian Mixture Model based Hierarchical Clustering is proposed for efficiently predicting the Autism Spectrum Disorder. Also, Flexible splitting concept was proposed for hierarchical clustering in order to increase the quality of guessing and classification accuracy. The proposed algorithm is validated to check the performance against the existing method. The results shows that the proposed algorithm outperforms the existing algorithm in terms of classification accuracy.

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