Granular Decision Tree and Evolutionary Neural SVM for Protein Secondary Structure Prediction | Zendy

Anjum Reyaz-Ahmed | Zendy; Yanqing Zhang | Zendy; Robert W. Harrison | Zendy

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Granular Decision Tree and Evolutionary Neural SVM for Protein Secondary Structure Prediction

Author(s) -

Anjum Reyaz-Ahmed,

Yanqing Zhang,

Robert W. Harrison

Publication year - 2009

Publication title -

international journal of computational intelligence systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.385

H-Index - 41

eISSN - 1875-6891

pISSN - 1875-6883

DOI - 10.1080/18756891.2009.9727666

Subject(s) - support vector machine , decision tree , computer science , artificial intelligence , artificial neural network , sliding window protocol , classifier (uml) , structured support vector machine , pattern recognition (psychology) , binary tree , granular computing , data mining , machine learning , binary classification , window (computing) , algorithm , rough set , operating system

A new sliding window scheme is introduced with multiple windows to form the protein data for SVM. Two new tertiary classifiers are introduced; one of them makes use of support vector machines as neurons in neural network architecture and the other tertiary classifier is a granular decision tree based on granular computing, decision tree and SVM. Binary classifier using multiple windows is compared with single window scheme. The accuracy levels of the new classifiers are better than most available techniques.

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