Abstract
This paper presents an analysis of moments of predictive deviations as measures of ensemble diversity to estimate the performance of time series prediction. As an extension of the ambiguity decomposition of bagging ensemble, we decompose the fourth power of ensemble prediction error and clarify the effect of the moments of predictive deviations of ensemble members to the ensemble prediction error. We utilize this analysis for estimating the performance of time sires prediction, and show the effectiveness by means of numerical experiments.
Keywords
- Moments of predictive deviations
- Ensemble diversity measures
- Performance estimation
- Time series prediction
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© 2012 Springer-Verlag Berlin Heidelberg
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Ono, K., Kurogi, S., Nishida, T. (2012). Moments of Predictive Deviations for Ensemble Diversity Measures to Estimate the Performance of Time Series Prediction. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_8
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DOI: https://doi.org/10.1007/978-3-642-34500-5_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34499-2
Online ISBN: 978-3-642-34500-5
eBook Packages: Computer ScienceComputer Science (R0)
