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
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;
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
DOI :
10.1109/CISE.2009.5365635
