A New Feature Selection Method Based On Cla-ec In Face Recognition System

2012 ◽  
Vol 04 (02) ◽  
pp. 159-171 ◽  
Author(s):  
Akhtar Hazrati Bishak ◽  
Karim Faez ◽  
Morteza Hazrati Bishak
Keyword(s):  
Feature Selection ◽  
Face Recognition ◽  
Feature Selection Method ◽  
Recognition System ◽  
Selection Method ◽  
Face Recognition System ◽  
New Feature

A lazy feature selection method for multi-label classification

2021 ◽  
Vol 25 (1) ◽  
pp. 21-34
Author(s):  
Rafael B. Pereira ◽  
Alexandre Plastino ◽  
Bianca Zadrozny ◽  
Luiz H.C. Merschmann
Keyword(s):  
Feature Selection ◽  
Text Categorization ◽  
Feature Selection Method ◽  
Selection Method ◽  
Video Classification ◽  
Classification Problems ◽  
Class Label ◽  
New Feature ◽  
Feature Selection Techniques ◽  
Biomolecular Analysis

In many important application domains, such as text categorization, biomolecular analysis, scene or video classification and medical diagnosis, instances are naturally associated with more than one class label, giving rise to multi-label classification problems. This has led, in recent years, to a substantial amount of research in multi-label classification. More specifically, feature selection methods have been developed to allow the identification of relevant and informative features for multi-label classification. This work presents a new feature selection method based on the lazy feature selection paradigm and specific for the multi-label context. Experimental results show that the proposed technique is competitive when compared to multi-label feature selection techniques currently used in the literature, and is clearly more scalable, in a scenario where there is an increasing amount of data.

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