期刊文献+

基于局部线性嵌入的小样本组合预测方法 被引量:5

下载PDF
导出
摘要 组合预测可以提高预测结果的稳定性。在样本容量较小时,基于权重估计的组合预测模型容易导致巨大的估计误差而影响预测效果;特别是在回归框架下,还可能出现预测模型多于用于组合预测的样本数量,导致回归系数无法估计的问题。文章将降维技术中基于流形假设的局部线性嵌入算法引入到小样本组合预测中,以改进基于回归组合模型的预测效果。
出处 《统计与决策》 CSSCI 北大核心 2015年第9期9-12,共4页 Statistics & Decision
基金 国家社会科学基金资助项目(11GJ003-072 12GJ003-119)
  • 相关文献

参考文献9

  • 1詹宇斌,殷建平,刘新旺,张国敏.流形学习中基于局部线性结构的自适应邻域选择[J].计算机研究与发展,2011,48(4):576-583. 被引量:11
  • 2Javier Herrero,Alfonso Valencia.A hierarchical unsupervised growing neural network for clustering gene expression patterns[J]. Bioinformatics . 2001
  • 3钟明,薛惠锋,梅觅.基于局部线性嵌入的最大散度矩阵算法[J].计算机工程,2011,37(12):176-178. 被引量:1
  • 4Roweis ST,Saul LK.Nonlinear dimensionality reduction by locally linear embedding. Science . 2000
  • 5Robert R. Andrawis,Amir F. Atiya,Hisham El-Shishiny.Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition[J]. International Journal of Forecasting . 2010 (3)
  • 6Spyros Makridakis,Michèle Hibon.The M3-Competition: results, conclusions and implications[J]. International Journal of Forecasting . 2000 (4)
  • 7O Kouropteva,,O Okun,MPietikainen.Selection of the Optimal Pa-rameter Value for the Locally Linear Embedding Algorithm. Proc.of the 1st Int.Conf.on Fuzzy Systems and Knowledge Disco-very . 2002
  • 8Xie L,Wei R X,Zhang D W.Synthesizing Judgment Matrix and Risk-odds Matrix for Small-sample CombinedForecasting. The IEEE International Conference on Industrial Engineering and Engineering Management . 2010
  • 9Robert R. Andrawis,Amir F. Atiya,Hisham El-Shishiny.Combination of long term and short term forecasts, with application to tourism demand forecasting[J]. International Journal of Forecasting . 2010 (3)

二级参考文献30

  • 1罗四维,赵连伟.基于谱图理论的流形学习算法[J].计算机研究与发展,2006,43(7):1173-1179. 被引量:76
  • 2詹德川,周志华.基于流形学习的多示例回归算法[J].计算机学报,2006,29(11):1948-1955. 被引量:16
  • 3邵超,黄厚宽,赵连伟.一种更具拓扑稳定性的ISOMAP算法[J].软件学报,2007,18(4):869-877. 被引量:20
  • 4Turk M A, Pentland A P. Eigenfaces for Recognition[J]. Journal of Cognitive Neuroscience, 1991, 3(1): 71-86.
  • 5Roweis S T, Saul K L. Nonlinear Dimensionality Reduction by Locally Linear Embedding[J]. Science, 2000, 290(5500): 2323- 2326.
  • 6Belkin M, Niyogi P. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation[J]. Neural Computation, 2003, 15(6): 1373-1396.
  • 7Liu Chengjun, Wechsler H. A Gabor Fecture Classifier for Face Recognition[C] //Proc. of the 8th IEEE International Conference on Computer Vision. Vancouver, British Columbia, Canada: IEEE Computer Society, 2001.
  • 8Jolliffe I T. Principal Component Analysis [M]. New York: Springer, 1989.
  • 9Cox T F, Cox M A A. Multidimensional Scaling [M]. Florida:Chapman and Hall, 1994.
  • 10Duda R O, Hart P E, Stork D G. Pattern Classification [M]. New York: John Wiley & Sons, 2001.

共引文献12

同被引文献51

引证文献5

二级引证文献19

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部