|Appears in Collections:||Computing Science and Mathematics Book Chapters and Sections|
|Peer Review Status:||Refereed|
|Title:||A Targeted Estimation of Distribution Algorithm Compared to Traditional Methods in Feature Selection|
|Citation:||Neumann G & Cairns D (2016) A Targeted Estimation of Distribution Algorithm Compared to Traditional Methods in Feature Selection In: Madani K, Dourado A, Rosa A, Filipe J, Kacprzyk J (ed.) Computational Intelligence: Revised and Selected Papers of the International Joint Conference, IJCCI 2013, Vilamoura, Portugal, September 20-22, 2013, Cham, Switzerland: Springer. 5th International Joint Conference on Computational Intellegience, IJCCI 2013, 20.9.2013 - 22.9.2013, Vilamoura, Portugal, pp. 83-103.|
|Keywords:||Estimation of distribution algorithms|
|Series/Report no.:||Studies in Computational Intelligence, 613|
|Abstract:||The Targeted Estimation of Distribution Algorithm (TEDA) introduces into an EDA/GA hybrid framework a ‘Targeting’ process, whereby the number of active genes, or ‘control points’, in a solution is driven in an optimal direction. For larger feature selection problems with over a thousand features, traditional methods such as forward and backward selection are inefficient. Traditional EAs may perform better but are slow to optimize if a problem is sufficiently noisy that most large solutions are equally ineffective and it is only when much smaller solutions are discovered that effective optimization may begin. By using targeting, TEDA is able to drive down the feature set size quickly and so speeds up this process. This approach was tested on feature selection problems with between 500 and 20,000 features using all of these approaches and it was confirmed that TEDA finds effective solutions significantly faster than the other approaches.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|B-2015-CompInt-TEDA-Feature.pdf||683.79 kB||Adobe PDF||Under Permanent Embargo Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.