Feature ranking through weights manipulations for artificial neural networks-based classifiers
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...
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: | |
Online Access: | http://irep.iium.edu.my/37854/ http://irep.iium.edu.my/37854/ http://irep.iium.edu.my/37854/ 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 |
Similar Items
-
Input significance analysis: feature ranking through synaptic weights manipulation for ANNS-based classifiers
by: Hassan, Raini, et al.
Published: (2017) -
Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier
by: Hassan, Raini, et al.
Published: (2017) -
Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers
by: Al-Qudah,, Dua’A Mahmoud, et al.
Published: (2017) -
Mobile Application for Classifying Palm Oil Bunch using RGB and Artificial Neural Network
by: Sayyidatina Al Hurul Aina, Alzahati, et al.
Published: (2016) -
Comparison of feature selection techniques in classifying stroke documents
by: Nur Syaza Izzati, Mohd Rafei, et al.
Published: (2019)