Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets. Olmo, J. L., Romero, C., Gibaja, E., & Ventura, S. Int. J. Computational Intelligence Systems, 8(6):1144–1164, 2015.
Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets [link]Paper  doi  bibtex   
@Article{DBLP:journals/ijcisys/OlmoRGV15,
  Title                    = {Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: {A} Case of Study with Educational Data Sets},
  Author                   = {Juan Luis Olmo and C. Romero and E. Gibaja and S. Ventura},
  Journal                  = {Int. J. Computational Intelligence Systems},
  Year                     = {2015},
  Number                   = {6},
  Pages                    = {1144--1164},
  Volume                   = {8},
  Bibsource                = {dblp computer science bibliography, http://dblp.org},
  Biburl                   = {http://dblp.uni-trier.de/rec/bib/journals/ijcisys/OlmoRGV15},
  DOI                      = {10.1080/18756891.2015.1113748},
  Keywords                 = {Educational Data Mining,Predicting Student Performance},
  Timestamp                = {Mon, 23 Nov 2015 15:41:55 +0100},
  URL                      = {http://dx.doi.org/10.1080/18756891.2015.1113748}
}

Downloads: 0