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HICSS
2006
IEEE
97views Biometrics» more  HICSS 2006»
15 years 6 months ago
Dynamically Optimizing Parameters in Support Vector Regression: An Application of Electricity Load Forecasting
This study develops a novel model, GA-SVR, for parameters optimization in support vector regression and implements this new model in a problem forecasting maximum electrical daily...
Chin-Chia Hsu, Chih-Hung Wu, Shih-Chien Chen, Kang...
NIPS
2004
15 years 1 months ago
Using the Equivalent Kernel to Understand Gaussian Process Regression
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show (1) how to appro...
Peter Sollich, Christopher K. I. Williams
ISMIS
2011
Springer
14 years 2 months ago
An Evolutionary Algorithm for Global Induction of Regression Trees with Multivariate Linear Models
In the paper we present a new evolutionary algorithm for induction of regression trees. In contrast to the typical top-down approaches it globally searches for the best tree struct...
Marcin Czajkowski, Marek Kretowski
SDM
2009
SIAM
172views Data Mining» more  SDM 2009»
15 years 9 months ago
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach.
This paper is concerned with the task of travel-time prediction for an arbitrary origin-destination pair on a map. Unlike most of the existing studies, which focus only on a parti...
Sei Kato, Tsuyoshi Idé
DKE
2007
88views more  DKE 2007»
14 years 12 months ago
Regression analysis for massive datasets
In this paper, a two-stage block hypothesis testing following the idea of Fan, Lin and Cheng (2004) is proposed for massive data regression analysis. Variables selection criteria ...
Tsai-Hung Fan, Dennis K. J. Lin, Kuang-Fu Cheng