参考文献/References:
[ 1] Dietterich T G. M ach ine learn ing research: four current d irections [ J]. A IM agazine, 1997, 18( 4): 97-136.
[ 2] Freund Y, SchapireR E. Exper im ents w ith a new boosting algor ithm [ C] / / Proceed ing s o f the 13th Internationa lConference on M achine Learning. San Francisco: Mo rgan K aufmann, 1996: 148-156.
[ 3] Bre iman L. Bagg ing pred icto rs[ J]. M ach ing Learning, 1996, 24( 2): 123-140.
[ 4] Zhou Z H, W u J, TangW. Ensem bling neural netw orks: m any cou ld be better than a ll[ J]. A rtific ia l Inte lligence, 2002, 137( 1 /2): 239-263.
[ 5] W e iss SM, Apte C, Dame rau F J. M ax im izing tex t-m in ing performance[ J] . IEEE Inte lligent System s, 1999, 14 ( 4): 63-69.
[ 6] Schapire R E, Singer Y. Boostexte r: a boosting-based system for tex t catego riza tion [ J]. M achine Learning, 2000, 39( 223): 135-168.
[ 7] Tum erK, Ghosh J. C lassifie r com bin ing: analytical resu lts and im plica tions[ C ] / / Proceeding o f the AAA I-96Wo rkshop on Integrating
Mu ltiple LearnedM odels for Im prov ing and Sca lingM achine Lear ing A lgorithm s. Portland: AAA I Press, 1996.
[ 8] W ang X iaogang, Tang X iaoou. Using random subspace to comb ine mu ltiple featu res for face recogn ition[ C] / / Pro ceeding o f
the 6th IEEE Internationa l Confe rence on Autom a tic Face and Gesture Recogn ition. Los A lam ito s: IEEE Com puter So ciety Press, 2004: 284-289.
[ 9] Bay S D. Comb ining nearest ne ighbor classifiers through m ultiple fea ture subsets[ C] / / Proceeding of the Proceed ings o f the
17 th Internationa l Con ference onM ach ine Learn ing. M adison, W I: M o rgan Kaufm ann, 1998: 37-45.
[ 10] Robe rt Bry lla. A ttr ibute bagg ing: im prov ing accuracy of c lassifier ensemb les by using random featu re subse ts[ J]. Pattern Recogn ition, 2003, 36( 6): 1 291-1 302.
[ 11] Lew is D D. Na ve ( Bayes) a t forty: the independence assumption in info rma tion retrieva[ C] / / Proceed ing s o f 10 th European Conference onM ach ine Lea rning. Chemn itz, DE: Springer Ver lag, 1998: 4-15.
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