摘要: Ensemble rule based classification methods have been popular for a while in the machine-learning literature (Hand, 1997). Given the advent of low-cost, high-computing power, we are curious to see how far can we go by repeating some basic learning process, obtaining a variety of possible inferences, and finally basing the global classification decision on some sort of ensemble summary. Some general benefits to this idea have been observed indeed, and we are gaining wider and deeper insights on exactly why this is the case in many fronts of interest.
irma-international.org参考文章(16)
Gianluigi Folino, Clara Pizzuti, Giandomenico Spezzano, Ensemble techniques for parallel genetic programming based classifiers european conference on genetic programming. pp. 59- 69 ,(2003) , 10.1007/3-540-36599-0_6
JEROME H. FRIEDMAN, NICHOLAS I. FISHER, Bump hunting in high-dimensional data Statistics and Computing. ,vol. 9, pp. 123- 143 ,(1999) , 10.1023/A:1008894516817
David J. Hand, Niall M. Adams, Mark G. Kelly, Multiple Classifier Systems Based on Interpretable Linear Classifiers multiple classifier systems. pp. 136- 147 ,(2001) , 10.1007/3-540-48219-9_14
Lashon B. Booker, Do We Really Need to Estimate Rule Utilities in Classifier Systems Lecture Notes in Computer Science. pp. 125- 142 ,(2000) , 10.1007/3-540-45027-0_6
Larry Bull, On Using Constructivism in Neural Classifier Systems parallel problem solving from nature. pp. 558- 567 ,(2002) , 10.1007/3-540-45712-7_54
Thomas H. Westerdale, Local Reinforcement and Recombination in Classifier Systems Evolutionary Computation. ,vol. 9, pp. 259- 281 ,(2001) , 10.1162/106365601750405993
Jerome Friedman, Trevor Hastie, Robert Tibshirani, Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors) Annals of Statistics. ,vol. 28, pp. 337- 407 ,(2000) , 10.1214/AOS/1016218223
Robert E. Schapire, Yoram Singer, Improved boosting algorithms using confidence-rated predictions conference on learning theory. ,vol. 37, pp. 80- 91 ,(1998) , 10.1145/279943.279960
Martin V. Butz, David E. Goldberg, Kurian Tharakunnel, Analysis and improvement of fitness exploitation in XCS: bounding models, tournament selection, and bilateral accuracy Evolutionary Computation. ,vol. 11, pp. 239- 277 ,(2003) , 10.1162/106365603322365298
Jorge Muruzábal, Combining statistical and reinforcement learning in rule-based classification Computational Statistics. ,vol. 16, pp. 341- 359 ,(2001) , 10.1007/S001800100071