Improvements to random forest methodology

[1]  L. Breiman.  Heuristics of instability and stabilization in model selection , 1996 .

[2]  Tin Kam Ho,et al.  The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  J. Friedman,et al.  On bagging and nonlinear estimation , 2007 .

[4]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[5]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[6]  Mahesh Pal,et al.  Random forest classifier for remote sensing classification , 2005 .

[7]  Jonathan R. M. Hosking,et al.  Partitioning Nominal Attributes in Decision Trees , 1999, Data Mining and Knowledge Discovery.

[8]  C Helma,et al.  Prediction of Adverse Drug Reactions Using Decision Tree Modeling , 2010, Clinical pharmacology and therapeutics.

[9]  Pierre Geurts,et al.  Extremely randomized trees , 2006, Machine Learning.

[10]  Steve Horvath,et al.  Tumor classification by tissue microarray profiling: random forest clustering applied to renal cell carcinoma , 2005, Modern Pathology.

[11]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[12]  Manish Kumar,et al.  Forecasting Stock Index Movement: A Comparison of Support Vector Machines and Random Forest , 2006 .

[13]  Mark R. Segal,et al.  Multivariate random forests , 2011, WIREs Data Mining Knowl. Discov..

[14]  Sinisa Pajevic,et al.  Short-term prediction of mortality in patients with systemic lupus erythematosus: classification of outcomes using random forests. , 2006, Arthritis and rheumatism.

[15]  Yung-Seop Lee,et al.  Enriched random forests , 2008, Bioinform..

[16]  R. Tibshirani,et al.  Improvements on Cross-Validation: The 632+ Bootstrap Method , 1997 .

[17]  E. Polley,et al.  Statistical Applications in Genetics and Molecular Biology Random Forests for Genetic Association Studies , 2011 .

[18]  B. Efron.  The Estimation of Prediction Error , 2004 .

[19]  Richard A. Olshen.  Remembering Leo Breiman , 2010 .

[20]  Leo Breiman,et al.  Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001 .

[21]  David S. Siroky.  Navigating Random Forests and related advances in algorithmic modeling , 2009 .

[22]  Yi Lin,et al.  Random Forests and Adaptive Nearest Neighbors , 2006 .

[23]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[24]  Yali Amit,et al.  Shape Quantization and Recognition with Randomized Trees , 1997, Neural Computation.

[25]  Peng Jiang,et al.  MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features , 2007, Nucleic Acids Res..

[26]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[27]  Hemant Ishwaran,et al.  Random Survival Forests , 2008, Wiley StatsRef: Statistics Reference Online.

[28]  Nicolai Meinshausen,et al.  Quantile Regression Forests , 2006, J. Mach. Learn. Res..

[29]  Agostino Di Ciaccio,et al.  Computational Statistics and Data Analysis Measuring the Prediction Error. a Comparison of Cross-validation, Bootstrap and Covariance Penalty Methods , 2022 .

[30]  Robert C. Glen,et al.  Random Forest Models To Predict Aqueous Solubility , 2007, J. Chem. Inf. Model..

[31]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.