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Feature ranking through weights manipulations for artificial neural networks-based classifiers

Hassan, Raini and Hassan, Wan Haslina and Alshaikhli, Imad Fakhri Taha and Ahmad, Salmiah and Alizadeh, Mojtaba (2014) Feature ranking through weights manipulations for artificial neural networks-based classifiers. In: 2014 Fifth International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2014), 27th-29th Jan. 2014, Langkawi, Kedah.

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Abstract

Artificial Neural Networks (ANNs) are often viewed as black box. This limits the comprehensive understanding on how it deals with input neuron/data, as well as how it reached a particular decision. Input significance analysis (ISA) refers to the process of understanding these input neurons/data. And since this work is on classification problem, hence similarly, this process can also be called feature selection; where the goal is to have a classifier that can predict accurately and at the same time, its structure is as simple as possible. This work is particularly interested with ISA methods that manipulate weights, where separately, correlations are also applied. The goal is to create feature ranking list that performed the best in the selected classifiers. For validation methods, memory recall validation and K-Fold cross-validation methods are used. The results show one classifier that uses one of the ISA methods are performing well for both validation methods.

Item Type: Conference or Workshop Item (Invited Papers)
Additional Information: 4964/37854
Uncontrolled Keywords: Keywords-feature selection, feature ranking, input significance analysis, artificial neural networks, multi-layer perceptron, evolving connectionist system, evolving fuzzy neural network, correlations, spearman, pearson, connection weights, garson’s algorithm
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Mechatronics Engineering
Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Ahmad Nazreen Mohd Shamsuri (PT)
Date Deposited: 25 Aug 2014 15:38
Last Modified: 20 Jun 2018 15:35
URI: http://irep.iium.edu.my/id/eprint/37854

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