A robust classification model with voting based feature selection for diagnosis of epilepsy

2015 ◽  
Author(s):  
Ali Hassan ◽  
Farhan Riaz ◽  
Abdul Basit
Keyword(s):  
Feature Selection ◽  
Classification Model ◽  
Robust Classification ◽  
Selection For

Feature Selection for Robust Classification of Crack and Drop Signals

2008 ◽  
Vol 8 (1) ◽  
pp. 59-70 ◽  
Author(s):  
Vassilios Kappatos ◽  
Evangelos Dermatas
Keyword(s):  
Feature Selection ◽  
Robust Classification ◽  
Selection For

scholarly journals Ensemble Feature Selection for Breast Cancer Classification using Microarray Data

2020 ◽  
Vol 23 (65) ◽  
pp. 100-114
Author(s):  
Supoj Hengpraprohm ◽  
Suwimol Jungjit
Keyword(s):  
Breast Cancer ◽  
Feature Selection ◽  
Cross Validation ◽  
Microarray Dataset ◽  
Classification Model ◽  
Cancer Data ◽  
Evaluation Functions ◽  
Selection For ◽  
Feature Selection Approach ◽  
Fold Cross Validation

For breast cancer data classification, we propose an ensemble filter feature selection approach named ‘EnSNR’. Entropy and SNR evaluation functions are used to find the features (genes) for the EnSNR subset. A Genetic Algorithm (GA) generates the classification ‘model’. The efficiency of the ‘model’ is validated using 10-Fold Cross-Validation re-sampling. The Microarray dataset used in our experiments contains 50,739 genes for each of 32 patients. When our proposed ‘EnSNR’ subset of features is used; as well as giving an enhanced degree of prediction accuracy and reducing the number of irrelevant features (genes), there is also a small saving of computer processing time.

Chicken Algorithm Based Feature Selection For Arabic Information Searching System

2019 ◽  
pp. 389
Author(s):  
زينب عبدالأمير ◽  
علياء كريم عبدالحسن
Keyword(s):  
Feature Selection ◽  
Information Searching ◽  
Selection For
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