Using Correlation to Improve Boosting Technique: An Application for Time Series Forecasting
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Souza:2006:ICTAI,
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author = "L. V. {de Souza} and A. T. R. Pozo and A. C. Neto",
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title = "Using Correlation to Improve Boosting Technique: An
Application for Time Series Forecasting",
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booktitle = "8th IEEE International Conference on Tools with
Artificial Intelligence, ICTAI '06",
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year = "2006",
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pages = "26--32",
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address = "Arlington, USA",
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month = nov,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-7695-2728-0",
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DOI = "doi:10.1109/ICTAI.2006.118",
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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",
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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