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HICSS
2006
IEEE
97views Biometrics» more  HICSS 2006»
14 years 2 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
13 years 10 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
12 years 11 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»
14 years 6 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»
13 years 8 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