Using Correlation to Improve Boosting Technique: An Application for Time Series Forecasting

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

@InProceedings{Souza:2006:ICTAI,
  author =       "L. V. {de Souza} and A. T. R. Pozo and A. C. Neto",
  title =        "Using Correlation to Improve Boosting Technique: An
                 Application for Time Series Forecasting",
  booktitle =    "8th IEEE International Conference on Tools with
                 Artificial Intelligence, ICTAI '06",
  year =         "2006",
  pages =        "26--32",
  address =      "Arlington, USA",
  month =        nov,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7695-2728-0",
  DOI =          "doi:10.1109/ICTAI.2006.118",
  abstract =     "Time series forecasting has been widely used to
                 support decision making, in this context a highly
                 accurate prediction is essential to ensure the quality
                 of the decisions. Ensembles of machines currently
                 receive a lot of attention; they combine predictions
                 from different forecasting methods as a procedure to
                 improve the accuracy. This paper explores genetic
                 programming and boosting technique to obtain an
                 ensemble of regressors and proposes a new formula for
                 the final hypothesis. This new formula is based on the
                 correlation coefficient instead of the geometric median
                 used by the boosting algorithm. To validate this
                 method, experiments were performed, the mean squared
                 error (MSE) has been used to compare the accuracy of
                 the proposed method against the results obtained by GP,
                 GP using a boosting technique and the traditional
                 statistical methodology (ARMA). The results show
                 advantages in the use of the proposed approach",
  notes =        "Dept. of Design, Fed. Univ. of Parana, Curitiba",
}

Genetic Programming entries for Luzia Vidal de Souza Aurora Trinidad Ramirez Pozo Anselmo Chaves Neto

Citations