Feature Selection ToolboxFST3 LibraryShare


  • 9th September 2012FST 3.1.1 corrects an indexing bug in Sparse ARFF input filter. Now the filter is compliant with Sparse ARFF specification. Standard ARFF filter is now less sensitive to header formatting and accepts more ARFF files right away.
  • 30th March 2011The most significant update planned for 2011 has been made public. See History for details on what is new in FST 3.1.
  • 13th January 2011Added Exhaustive Search (standard + threaded versions) to enable optimal feature selection. Improved result tracking and LibSVM 3.0 support.
  • 2nd November 2010Improved support for ARFF data format. All code polished to enable compilation under Visual C++ (in addition to Linux/Cygwin gcc).
Archive (10)


  • udit [Mar 6th 2014]i use it
  • JuBeOr [Dec 30th 2013]For me is impressive the amount of work the UTIA have made to help everyone solving problems all around the world. I want to express my gratitude from Spain.
  • Nad [Sep 24th 2013]Hello, I wish to know how the Feature Selection Technic can be implemented to signals
Complete guestbook (12)


  • additional criteria + additional search schemes (Simulated Annealing...)
  • hierarchical sub-space access (to enable FS method chaining)
  • regression based wrappers
  • mixture models with embedded feature selection
  • ...your suggestions ?

Feature Selection Toolbox 3 (FST3) is a standalone widely applicable C++ library for feature selection (FS, also known as attribute or variable selection), capable of reducing problem dimensionality to maximize the accuracy of data models, performance of automatic decision rules as well as to reduce data acquisition cost. The library can be exploited by users in research as well as in industry. Less experienced users can experiment with different provided methods and their application to reallife problems, experts can implement their own criteria or search schemes taking advantage of the toolbox framework.

FST3 key functionality:

FST3 (v3.1) functionality in more detail: