TY - GEN
T1 - Study on kernel partial least squares based key indicator prediction
AU - Yin, Shen
AU - Wang, Mingyu
AU - Luo, Hao
AU - Gao, Huijun
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - Kernel method has been applied to many multivariate statistical analysis techniques. In this paper, we investigated the regression properties of Kernel Partial Least Squares (KPLS) and compared it to the standard technique. Basic mathematical algorithms and application of KPLS were shown. We further established regression model based on KPLS and demonstrated the model by a numerical case.
AB - Kernel method has been applied to many multivariate statistical analysis techniques. In this paper, we investigated the regression properties of Kernel Partial Least Squares (KPLS) and compared it to the standard technique. Basic mathematical algorithms and application of KPLS were shown. We further established regression model based on KPLS and demonstrated the model by a numerical case.
UR - https://www.scopus.com/pages/publications/84973097837
U2 - 10.1109/IECON.2015.7392562
DO - 10.1109/IECON.2015.7392562
M3 - 会议稿件
AN - SCOPUS:84973097837
T3 - IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
SP - 3016
EP - 3021
BT - IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015
Y2 - 9 November 2015 through 12 November 2015
ER -