Title :
Enhancing Boosting by Feature Non-Replacement for Microarray Data Analysis
Author :
Guile, Geoffrey R. ; Wang, Wenjia
Author_Institution :
Univ. of East Anglia, Norwich
Abstract :
We have investigated strategies for enhancing ensemble learning algorithms for DNA microarray data analysis. By using modified versions of AdaBoost, LogitBoost and BagBoosting we have shown that feature non-replacement provides an effective enhancement to the performance of all three algorithms, and overall, BagBoosting with feature non-replacement had the lowest error rates when used on six commonly-used cancer datasets.
Keywords :
DNA; biology computing; data analysis; learning (artificial intelligence); AdaBoost; BagBoosting; DNA microarray data analysis; LogitBoost; cancer datasets; ensemble learning algorithms; feature nonreplacement; Bagging; Boosting; Cancer; DNA; Data analysis; Diseases; Error analysis; Iterative algorithms; Neural networks; Voting;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4370995
