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

• Main Authors: Hassan, Raini, Hassan, Wan Haslina, Alshaikhli, Imad Fakhri Taha, Ahmad, Salmiah, Alizadeh, Mojtaba
• Other Authors: Al-Dabass, David
• Format: Conference or Workshop Item
• Language: English; English
• Published: The Institute of Electrical and Electronics Engineers 2014
• Subjects: T Technology (General)
• Online Access: http://irep.iium.edu.my/37854/1/Feature_Ranking_Through_Weights_Manipulations_for_Artificial_Neural_Networks-.pdf; http://irep.iium.edu.my/37854/4/37854.pdf; http://irep.iium.edu.my/37854/; http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7280896
• Institution: Universiti Islam Antarabangsa Malaysia

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. An...