Hierarchical Clustering Support Vector Machines for Classifying Type-2 Diabetes Patients

Bioinformatics Research and Applications - Lecture Notes in Computer Science ◽

10.1007/978-3-540-79450-9_35 ◽

2008 ◽

pp. 379-389

Author(s):

Wei Zhong ◽

Rick Chow ◽

Richard Stolz ◽

Jieyue He ◽

Marsha Dowell

Keyword(s):

Type 2 Diabetes ◽

Support Vector Machines ◽

Hierarchical Clustering ◽

Support Vector ◽

Vector Machines ◽

Diabetes Patients

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DESIGN OF DECISION TREE VIA KERNELIZED HIERARCHICAL CLUSTERING FOR MULTICLASS SUPPORT VECTOR MACHINES

Cybernetics & Systems ◽

10.1080/01969720601139058 ◽

2007 ◽

Vol 38 (2) ◽

pp. 187-202 ◽

Author(s):

Zhao Lu ◽

Feng Lin ◽

Hao Ying

Keyword(s):

Support Vector Machines ◽

Decision Tree ◽

Hierarchical Clustering ◽

Support Vector ◽

Vector Machines ◽

Multiclass Support Vector Machines

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Comparison of Modified Hierarchical Clustering Based on Density Peaks Using Kernel Function with Support Vector Machines in the Classification of Sinusitis

Advances in Intelligent Systems and Computing - Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) ◽

10.1007/978-3-030-36674-2_21 ◽

2020 ◽

pp. 194-201

Author(s):

Zuherman Rustam ◽

Sri Hartini ◽

Nadisa Karina Putri ◽

Jacob Pandelaki

Keyword(s):

Support Vector Machines ◽

Hierarchical Clustering ◽

Kernel Function ◽

Support Vector ◽

Density Peaks ◽

Vector Machines

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Classification Of Diabetes Patients Using Kernel Based Support Vector Machines

2020 International Conference on Computer Communication and Informatics (ICCCI) ◽

10.1109/iccci48352.2020.9104185 ◽

2020 ◽

Author(s):

G. A. Pethunachiyar

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Diabetes Patients

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A novel intrusion detection system based on hierarchical clustering and support vector machines

Expert Systems with Applications ◽

10.1016/j.eswa.2010.06.066 ◽

2011 ◽

Vol 38 (1) ◽

pp. 306-313 ◽

Author(s):

Shi-Jinn Horng ◽

Ming-Yang Su ◽

Yuan-Hsin Chen ◽

Tzong-Wann Kao ◽

Rong-Jian Chen ◽

...

Keyword(s):

Support Vector Machines ◽

Intrusion Detection ◽

Hierarchical Clustering ◽

Intrusion Detection System ◽

Detection System ◽

Support Vector ◽

Vector Machines

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Type-2 fuzzy logic-based classifier fusion for support vector machines

Applied Soft Computing ◽

10.1016/j.asoc.2007.02.019 ◽

2008 ◽

Vol 8 (3) ◽

pp. 1222-1231 ◽

Author(s):

Xiujuan Chen ◽

Yong Li ◽

Robert Harrison ◽

Yan-Qing Zhang

Keyword(s):

Fuzzy Logic ◽

Support Vector Machines ◽

Classifier Fusion ◽

Support Vector ◽

Vector Machines

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Designing hybrid classifiers based on general type-2 fuzzy logic and support vector machines

Soft Computing ◽

10.1007/s00500-020-05052-x ◽

2020 ◽

Vol 24 (23) ◽

pp. 18009-18019 ◽

Author(s):

Emanuel Ontiveros ◽

Patricia Melin ◽

Oscar Castillo

Keyword(s):

Fuzzy Logic ◽

Support Vector Machines ◽

General Type ◽

Support Vector ◽

Vector Machines ◽

Hybrid Classifiers

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Classification of epilepsy seizure phase using interval type-2 fuzzy support vector machines

Neurocomputing ◽

10.1016/j.neucom.2016.03.033 ◽

2016 ◽

Vol 199 ◽

pp. 66-76 ◽

Author(s):

Udeme Ekong ◽

H.K. Lam ◽

Bo Xiao ◽

Gaoxiang Ouyang ◽

Hongbin Liu ◽

...

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Fuzzy Support Vector Machines ◽

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A new intrusion detection system using support vector machines and hierarchical clustering

The VLDB Journal ◽

10.1007/s00778-006-0002-5 ◽

2006 ◽

Vol 16 (4) ◽

pp. 507-521 ◽

Author(s):

Latifur Khan ◽

Mamoun Awad ◽

Bhavani Thuraisingham

Keyword(s):

Support Vector Machines ◽

Intrusion Detection ◽

Hierarchical Clustering ◽

Intrusion Detection System ◽

Detection System ◽

Support Vector ◽

Vector Machines

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Overlapping Clusters and Support Vector Machines Based Interval Type-2 Fuzzy System for the Prediction of Peptide Binding Affinity

IEEE Access ◽

10.1109/access.2019.2910078 ◽

2019 ◽

Vol 7 ◽

pp. 49756-49764 ◽

Author(s):

Volkan Uslan ◽

Huseyin Seker ◽

Robert John

Keyword(s):

Support Vector Machines ◽

Binding Affinity ◽

Fuzzy System ◽

Peptide Binding ◽

Support Vector ◽

Overlapping Clusters ◽

Vector Machines ◽

Interval Type ◽

Peptide Binding Affinity

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zSlices-Based General Type-2 Fuzzy Fusion of Support Vector Machines With Application to Bearing Fault Detection

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2017.2688963 ◽

2017 ◽

Vol 64 (9) ◽

pp. 7210-7217 ◽

Author(s):

Hossein Hassani ◽

Jafar Zarei ◽

Mohammad Mehdi Arefi ◽

Roozbeh Razavi-Far

Keyword(s):

Support Vector Machines ◽

Fault Detection ◽

General Type ◽

Support Vector ◽

Bearing Fault ◽

Bearing Fault Detection ◽

Vector Machines ◽

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