Now showing items 1-4 of 4

  • Clustering and nearest neighbour based classification approach for mobile activity recognition. 

    Bashir, Sulaimon A.; Doolan, Daniel C.; Petrovski, Andrei (Rinton Press http://www.rintonpress.com/xjmm12/jmm-12-12/110-124.pdf, 2016-04-08)
    BASHIR, S.A., DOOLAN, D.C. and PETROVSKI, A. 2016. Clustering and nearest neighbour based classification approach for mobile activity recognition. Journal of mobile multimedia [online], 12 (1/2), pages 100-124. Available from: http://www.rintonpress.com/xjmm12/jmm-12-12/110-124.pdf
    We present a hybridized algorithm based on clustering and nearest neighbour classifier for mobile activity recognition. The algorithm transforms a training dataset into a more compact and reduced representative set that ...
  • A fine-grained random forests using class decomposition: an application to medical diagnosis. 

    Elyan, Eyad; Gaber, Mohamed Medhat (Springer http://dx.doi.org/10.1007/s00521-015-2064-z, 2015-09-22)
    ELYAN, E. and GABER, M.M. 2015. A fine-grained random forests using class decomposition: an application to medical diagnosis. Neural computing and applications [online], FirstOnline. Available from: http://dx.doi.org/10.1007/s00521-015-2064-z
    Class decomposition describes the process of segmenting each class into a number of homogeneous subclasses. This can be naturally achieved through clustering. Utilising class decomposition can provide a number of benefits ...
  • On pruning and feature engineering in Random Forests. 

    Fawagreh, Khaled (Robert Gordon University Faculty of Design and Technology, School of Computing Science and Digital Media, 2016-10-01)
    FAWAGREH, K. 2016. On pruning and feature engineering in Random Forests. Robert Gordon University, PhD thesis.
    Random Forest (RF) is an ensemble classification technique that was developed by Leo Breiman over a decade ago. Compared with other ensemble techniques, it has proved its accuracy and superiority. Many researchers, ...
  • Relation discovery from web data for competency management. 

    Zhu, Jianhan; Goncalves, Alexandre L.; Uren, Victoria; Motta, Enrico; Pacheco, Roberto; Eisenstadt, Marc; Song, Dawei (IOS Press, 2007-12)
    ZHU, J., GONCALVES, A. L., UREN, V. S., MOTTA, E., PACHECO, R., EISENSTADT, M. and SONG, D., 2007. Relation discovery from web data for competency management. Web Intelligence and Agent Systems, 5 (4), pp. 405-417.
    In current organizations, valuable enterprise knowledge is often buried under rapidly expanding huge amount of unstructured information in the form of web pages, blogs, and other forms of human text communications. ...