On Some Feature Selection Strategies for Spam Filter Design

2006 ◽  
Author(s):  
Ren Wang ◽  
Amr Youssef ◽  
Ahmed Elhakeem
Keyword(s):  
Feature Selection ◽  
Filter Design ◽  
Spam Filter ◽  
Selection Strategies

Feature Selection Strategies and Perceptual Expertise in Configuration Search Tasks

2011 ◽  
Author(s):  
Lindsey M. Kitchell ◽  
Francisco J. Parada ◽  
Brandi L. Emerick ◽  
Tom A. Busey
Keyword(s):  
Feature Selection ◽  
Perceptual Expertise ◽  
Search Tasks ◽  
Selection Strategies

scholarly journals Feature selection strategies for drug sensitivity prediction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Krzysztof Koras ◽  
Dilafruz Juraeva ◽  
Julian Kreis ◽  
Johanna Mazur ◽  
Eike Staub ◽  
...  
Keyword(s):  
Feature Selection ◽  
Drug Sensitivity ◽  
Selection Strategies ◽  
Drug Sensitivity Prediction

scholarly journals EMAIL SPAM DETECTION: A SYMBIOTIC FEATURE SELECTION APPROACH FOSTERED BY EVOLUTIONARY COMPUTATION

2013 ◽  
Vol 12 (04) ◽  
pp. 863-884 ◽  
Author(s):  
PEDRO SOUSA ◽  
PAULO CORTEZ ◽  
RUI VAZ ◽  
MIGUEL ROCHA ◽  
MIGUEL RIO
Keyword(s):  
Feature Selection ◽  
Electronic Mail ◽  
Evaluation Procedure ◽  
Internet Service ◽  
Selection Strategies ◽  
Internet Users ◽  
Selection Approach ◽  
Spam Filters ◽  
Inherent Problem ◽  
Feature Selection Approach

The electronic mail (email) is nowadays an essential communication service being widely used by most Internet users. One of the main problems affecting this service is the proliferation of unsolicited messages (usually denoted by spam) which, despite the efforts made by the research community, still remains as an inherent problem affecting this Internet service. In this perspective, this work proposes and explores the concept of a novel symbiotic feature selection approach allowing the exchange of relevant features among distinct collaborating users, in order to improve the behavior of anti-spam filters. For such purpose, several Evolutionary Algorithms (EA) are explored as optimization engines able to enhance feature selection strategies within the anti-spam area. The proposed mechanisms are tested using a realistic incremental retraining evaluation procedure and resorting to a novel corpus based on the well-known Enron datasets mixed with recent spam data. The obtained results show that the proposed symbiotic approach is competitive also having the advantage of preserving end-users privacy.

Drug and Nondrug Classification Based on Deep Learning with Various Feature Selection Strategies

2018 ◽  
Vol 13 (3) ◽  
pp. 253-259 ◽  
Author(s):  
Long Yu ◽  
Xia Sun ◽  
Shengwei Tian ◽  
Xinyu Shi ◽  
Yilin Yan
Keyword(s):  
Feature Selection ◽  
Deep Learning ◽  
Selection Strategies
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