The Neural Network with Automatic Feature Selection for Solving Problems with Categorical Variables

2018 ◽  
pp. 129-135 ◽  
Author(s):  
Yuriy S. Fedorenko ◽  
Yuriy E. Gapanyuk
Keyword(s):  
Neural Network ◽  
Feature Selection ◽  
Categorical Variables ◽  
The Neural Network ◽  
Selection For ◽  
Automatic Feature Selection

ROUGH FEATURE SELECTION FOR NEURAL NETWORK BASED IMAGE CLASSIFICATION

2002 ◽  
Vol 02 (04) ◽  
pp. 541-555 ◽  
Author(s):  
CHANGJING SHANG ◽  
QIANG SHEN
Keyword(s):  
Neural Network ◽  
Feature Selection ◽  
Image Classification ◽  
Rough Set ◽  
Reduction Method ◽  
Feature Reduction ◽  
Neural Network Classifier ◽  
The Neural Network ◽  
Study Results ◽  
Selection For

Effective feature selection is essential to the development of any intelligent classifier which is intended for use in high-dimension domains. This paper presents an approach that incorporates a rough set-assisted feature reduction method and a neural network-based classifier for image classification. The approach minimises the need for feature extraction without altering the underlying semantics of the features chosen. Through the proposed integration the size of the neural network classifier, which is sensitive to the dimensionality of the dataset, becomes manageable and the network is able to classify images that would otherwise require many more features to represent. Comparative study results from realistic applications demonstrate the success of this work.

Automatic feature selection for unsupervised image segmentation

2000 ◽  
Vol 77 (8) ◽  
pp. 1230-1232 ◽  
Author(s):  
W. Al-Nuaimy ◽  
Y. Huang ◽  
A. Eriksen ◽  
V. T. Nguyen
Keyword(s):  
Feature Selection ◽  
Image Segmentation ◽  
Selection For ◽  
Unsupervised Image Segmentation ◽  
Automatic Feature Selection
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