Learning similarity functions for binary strings via genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Pebriadi:2016:ICACSIS,
  author =       "M. S. Pebriadi and V. Dewanto and W. A. Kusuma and 
                 F. M. Afendi and R. Heryanto",
  booktitle =    "2016 International Conference on Advanced Computer
                 Science and Information Systems (ICACSIS)",
  title =        "Learning similarity functions for binary strings via
                 genetic programming",
  year =         "2016",
  pages =        "476--483",
  abstract =     "Data that encode the presence of some characteristics
                 typically can be represented as binary strings. We need
                 similarity functions for binary strings in order to
                 classify or cluster them. Existing similarity
                 functions, however, do not take advantage of training
                 data, which are often available. We believe that
                 similarity functions should be data-specific. To this
                 end, we use genetic programming (GP) to learn
                 similarity functions from training data. We propose a
                 novel fitness function that considers five aspects of
                 good similarity functions, i.e. recall, magnitude,
                 zero-division, identity and symmetry. We also report
                 mostly-used maths operators from extensive literature
                 review. Experiment results show that GP-based
                 similarity functions outperform the well-known Tanimoto
                 function in most datasets in terms of classification
                 accuracy using SVMs. In addition, those GP-based
                 similarity functions are simpler: using fewer numbers
                 of operators and operands. This suggests that our
                 proposed fitness function for GP is justifiable for
                 learning similarity functions.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICACSIS.2016.7872773",
  month =        oct,
  notes =        "Also known as \cite{7872773}",
}

Genetic Programming entries for M S Pebriadi V Dewanto W A Kusuma F M Afendi R Heryanto

Citations