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This paper examines from an experimental perspective random forests, the increasingly used statistical method for classification and regression problems introduced by Leo Breiman in 2001.
Breiman L., Friedman J.H., Olshen R.A., Stone C.J. (1984) Classification And Regression Trees . Chapman & Hall
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Breiman, L. (1996) Bagging predictors . Machine Learning, 26(2):123-140
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Alon U., Barkai N., Notterman D.A., Gish K., Ybarra S., Mack D., and Levine A.J. (1999) Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays . Proc Natl Acad Sci USA, Cell Biology, 96(12):6745-6750
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Dietterich, T. (1999) An experimental comparison of three methods for constructing ensembles of decision trees : Bagging, Boosting and randomization . Machine Learning, 1-22
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Golub T.R., Slonim D.K, Tamayo P., Huard C., Gaasenbeek M., Mesirov J.P., Coller H., Loh M.L., Downing J.R., Caligiuri M.A., Bloomfield C.D., and Lander E.S. (1999) Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring . Science, 286:531-537
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Dietterich, T. (2000) Ensemble Methods in Machine Learning . Lecture Notes in Computer Science, 1857:1-15
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Ross D.T., Scherf U., Eisen M.B., Perou C.M., Rees C., Spellman P., Iyer V., Jeffrey S.S., de Rijn M.V., Waltham M., Pergamenschikov A., Lee J.C., Lashkari D., Shalon D., Myers T.G., Weinstein J.N., Botstein D., Brown P.O. (2000) Systematic variation in gene expression patterns in human cancer cell lines . Nature Genetics, 24(3):227-235
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Breiman L. (2001) Random Forests . Machine Learning, 45:5-32
2001
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Cutler A. and Zhao G. (2001) Pert - Perfect random tree ensembles . Computing Science and Statistics, 33:490-497
2001
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Hastie T., Tibshirani R., Friedman J. (2001) The Elements of Statistical Learning . Springer
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Khan J., Wei J.S., Ringner M., Saal L.H., Ladanyi M., Westermann F., Berthold F., Schwab M., Antonescu C.R., Peterson C., Meltzer P.S. (2001) Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks . Nat Med, 7:673-679
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Bühlmann, P. and Yu, B. (2002) Analyzing Bagging . The Annals of Statistics, 30(4):927-961
2002
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Guyon I., Weston J., Barnhill S., and Vapnik V.N. (2002) Gene selection for cancer classification using support vector machines . Machine Learning, 46(1-3):389-422
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Liaw A. and Wiener M. (2002). Classification and Regression by randomForest . R News, 2(3):18-22
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Efron B., Hastie T., Johnstone I., and Tibshirani R. (2004) Least angle regression . Annals of Statistics, 32(2):407-499
2004
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Breiman L. and Cutler, A. (2005) Random Forests . Berkeley, http://www.stat.berkeley.edu/users/breiman/RandomForests/
2005
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Díaz-Uriarte R. and Alvarez de Andrés S. (2006) Gene Selection and classification of microarray data using random forest . BMC Bioinformatics, 7:3, 1-13
2006
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Grömping U. (2006) Relative Importance for Linear Regression in R: The Package relaimpo . Journal of Statistical Software 17, Issue 1
2006
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Poggi J.M. and Tuleau C. (2006) Classification supervisée en grande dimension. Application à l’agrément de conduite automobile . Revue de Statistique Appliquée, LIV(4):39-58
2006
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Pomeroy S.L., Tamayo P., Gaasenbeek M., Sturla L.M., Angelo M., McLaughlin M.E., Kim J.Y., Goumnerova L.C., Black P.M., Lau C., Allen J.C., Zagzag D., Olson J.M., Curran T., Wetmore C., Biegel J.A., Poggio T., Mukherjee S., Rifkin R., Califano A., Stolovitzky G., Louis D.N., Mesirov J.P., Lander E.S., Golub T.R. (2002) Prediction of central nervous system embryonal tumour outcome based on gene expression . Nature, 415:436-442
2002
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Singh D., Febbo P.G., Ross K., Jackson D.G., Manola J., Ladd C., Tamayo P., Renshaw A.A., D’Amico A.V., Richie J.P., Lander E.S., Loda M., Kantoff P.W., Golub T.R., and Sellers W.R. (2002) Gene expression correlates of clinical prostate cancer behavior . Cancer Cell, 1:203-209
2002
Cited alongside, same era.
van’t Veer L.J., Dai H., van de Vijver M.J., He Y.D., Hart A.A.M., Mao M., Peterse H.L., van der Kooy K., Marton M.J., Witteveen A.T., Schreiber G.J., Kerkhoven R.M., Roberts C., Linsley P.S., Bernards R., Friend S.H. (2002) Gene expression profiling predicts clinical outcome of breast cancer . Nature, 415:530-536
2002
Cited alongside, same era.
Cheze N., Poggi J.M. and Portier B. (2003) Partial and Recombined Estimators for Nonlinear Additive Models . Statistical Inference for Stochastic Processes, Vol. 6, 2, 155-197
2003
Cited alongside, same era.
Guyon I. and Elisseff A. (2003) An introduction to variable and feature selection . Journal of Machine Learning Research, 3:1157-1182
2003
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Rakotomamonjy A. (2003) Variable selection using SVM-based criteria . Journal of Machine Learning Research, 3:1357-1370
2003
Cited alongside, same era.
Ramaswamy S., Ross K.N., Lander E.S., Golub T.R. (2003) A molecular signature of metastasis in primary solid tumors . Nature Genetics, 33:49-54
2003
Cited alongside, same era.
2003
Cited alongside, same era.
Later among the works it cites.
Grömping U. (2007) Estimators of Relative Importance in Linear Regression Based on Variance Decomposition . The American Statistician 61:139-147
2007
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Park M.Y. and Hastie T. (2007) An L1 regularization-path algorithm for generalized linear models . J. Roy. Statist. Soc. Ser. B, 69:659-677
2007
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Strobl C., Boulesteix A.-L., Zeileis A. and Hothorn T. (2007) Bias in random forest variable importance measures: illustrations, sources and a solution . BMC Bioinformatics, 8:25
2007
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Archer K.J. and Kimes R.V. (2008) Empirical characterization of random forest variable importance measures . Computational Statistics & Data Analysis 52:2249-2260
2008
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Ben Ishak A. and Ghattas B. (2008) Sélection de variables en classification binaire : comparaisons et application aux données de biopuces . To appear, Revue SFDS-RSA
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Fan J. and Lv J. (2008) Sure independence screening for ultra-high dimensional feature space . J. Roy. Statist. Soc. Ser. B, 70:849-911
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Strobl C., Boulesteix A.-L., Kneib T., Augustin T. and Zeileis A. (2008) Conditional variable importance for Random Forests . BMC Bioinformatics, 9:307
2008
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Biau G., Devroye L., and Lugosi G. (2008) Consistency of random forests and other averaging classifiers . Journal of Machine Learning Research, 9:2039-2057
2057
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