Feature Selection for Neural Networks Through Binomial Regression

2006 ◽  
pp. 737-745
Author(s):  
Gecynalda Soares S. Gomes ◽  
Teresa B. Ludermir
Keyword(s):  
Neural Networks ◽  
Feature Selection ◽  
Binomial Regression ◽  
Selection For

Redundancy-Controlled Feature Selection for Fuzzy Neural Networks

2021 ◽  
Author(s):  
Tao Gao ◽  
Xiao Bai ◽  
Liang Zhang ◽  
Chen Wang ◽  
Jian Wang
Keyword(s):  
Neural Networks ◽  
Feature Selection ◽  
Fuzzy Neural Networks ◽  
Fuzzy Neural ◽  
Selection For

Feature Selection for Neural Networks Using Group Lasso Regularization

2020 ◽  
Vol 32 (4) ◽  
pp. 659-673 ◽  
Author(s):  
Huaqing Zhang ◽  
Jian Wang ◽  
Zhanquan Sun ◽  
Jacek M. Zurada ◽  
Nikhil R. Pal
Keyword(s):  
Neural Networks ◽  
Feature Selection ◽  
Group Lasso ◽  
Selection For

scholarly journals A GMDH-type neural network with multi-filter feature selection for the prediction of transition temperatures of bent-core liquid crystals

RSC Advances ◽  
2016 ◽  
Vol 6 (102) ◽  
pp. 99676-99684 ◽  
Author(s):  
Davor Antanasijević ◽  
Jelena Antanasijević ◽  
Viktor Pocajt ◽  
Gordana Ušćumlić
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Feature Selection ◽  
Transition Temperatures ◽  
Chi Square ◽  
Qspr Study ◽  
Selection For ◽  
Filter Approach ◽  
Selection Of Descriptors ◽  
Selection Of

The QSPR study on transition temperatures of five-ring bent-core LCs was performed using GMDH-type neural networks. A novel multi-filter approach, which combines chi square ranking, v-WSH and GMDH algorithm was used for the selection of descriptors.

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