Gene selection algorithm combining ReliefF and relative neighborhood rough set

2011 ◽  
Author(s):  
Jiu-cheng Xu ◽  
Ling-jun Zhang ◽  
Lin Sun ◽  
Yun-peng Gao
Keyword(s):  
Rough Set ◽  
Gene Selection ◽  
Selection Algorithm ◽  
Neighborhood Rough Set ◽  
Gene Selection Algorithm

A Comparative Analysis of Rough Set Based Intelligent Techniques for Unsupervised Gene Selection

2013 ◽  
Vol 2 (4) ◽  
pp. 33-46 ◽  
Author(s):  
P. K. Nizar Banu ◽  
H. Hannah Inbarani
Keyword(s):  
Data Mining ◽  
Rough Set ◽  
Gene Selection ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Huge Number ◽  
Number Of Genes ◽  
Micro Array ◽  
Tolerance Rough Set ◽  
Array Databases

As the micro array databases increases in dimension and results in complexity, identifying the most informative genes is a challenging task. Such difficulty is often related to the huge number of genes with very few samples. Research in medical data mining addresses this problem by applying techniques from data mining and machine learning to the micro array datasets. In this paper Unsupervised Tolerance Rough Set based Quick Reduct (U-TRS-QR), a diverse feature selection algorithm, which extends the existing equivalent rough sets for unsupervised learning, is proposed. Genes selected by the proposed method leads to a considerably improved class predictions in wide experiments on two gene expression datasets: Brain Tumor and Colon Cancer. The results indicate consistent improvement among 12 classifiers.

Fast feature selection algorithm for neighborhood rough set model based on Bucket and Trie structures

2019 ◽  
Vol 5 (3) ◽  
pp. 329-347 ◽  
Author(s):  
Rachid Benouini ◽  
Imad Batioua ◽  
Soufiane Ezghari ◽  
Khalid Zenkouar ◽  
Azeddine Zahi
Keyword(s):  
Feature Selection ◽  
Rough Set ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Model Based ◽  
Neighborhood Rough Set
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