DocumentCode
2854955
Title
Optimal-Weight Selection for Regressor Ensemble
Author
An, Kun ; Meng, Jiang
Author_Institution
Sch. of Inf. & Commun. Eng., North Univ. of China, Taiyuan, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
A novel selective combination, optimal-weight selective ensemble (OPSEN) algorithm, is provided for the ensemble in regression tasks. It adopts the selective strategy with optimal weight matrix, whose column is the best vector corresponding to a certain training sample and can calculate the output as close to the sample target as possible. Experiment results show OPSEN is quite effective for regressor ensembles and can be regarded as a tradeoff approach between bagging and GASEN, two popular and good ensembling methods.
Keywords
learning (artificial intelligence); matrix algebra; regression analysis; optimal weight matrix; optimal-weight selective ensemble algorithm; regressor ensemble; Aggregates; Bagging; Boosting; Diversity reception; Genetic algorithms; Mechanical engineering; Testing; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5365635
Filename
5365635
Link To Document