ipred

R package ipred: Improved Predictors. Improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.

Keywords for this software

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References in zbMATH (referenced in 28 articles )

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  1. Genuer, Robin; Poggi, Jean-Michel: Random forests with R (2020)
  2. Khan, Zardad; Gul, Asma; Perperoglou, Aris; Miftahuddin, Miftahuddin; Mahmoud, Osama; Adler, Werner; Lausen, Berthold: Ensemble of optimal trees, random forest and random projection ensemble classification (2020)
  3. Ribeiro, Rita P.; Moniz, Nuno: Imbalanced regression and extreme value prediction (2020)
  4. Ramasubramanian, Karthik; Singh, Abhishek: Machine learning using R. With time series and industry-based use cases in R (2019)
  5. Gul, Asma; Perperoglou, Aris; Khan, Zardad; Mahmoud, Osama; Miftahuddin, Miftahuddin; Adler, Werner; Lausen, Berthold: Ensemble of a subset of (k)NN classifiers (2018)
  6. Penning de Vries, Bas B. L.; van Smeden, Maarten; Groenwold, Rolf H. H.: Propensity score estimation using classification and regression trees in the presence of missing covariate data (2018)
  7. Van der Laan, Mark J.; Rose, Sherri: Targeted learning in data science. Causal inference for complex longitudinal studies (2018)
  8. Conversano, Claudio; Dusseldorp, Elise: Modeling threshold interaction effects through the logistic classification trunk (2017)
  9. Audigier, Vincent; Husson, François; Josse, Julie: A principal component method to impute missing values for mixed data (2016)
  10. Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jakob; Studerus, Erich; Casalicchio, Giuseppe; Jones, Zachary M.: mlr: machine learning in (\mathbfR) (2016)
  11. Cichosz, Paweł: Data mining algorithms. Explained using R (2015)
  12. Robin Genuer, Jean-Michel Poggi, Christine Tuleau-Malot: VSURF: An R Package for Variable Selection Using Random Forests (2015) not zbMATH
  13. Zhou, Yan; McArdle, John J.: Rationale and applications of survival tree and survival ensemble methods (2015)
  14. Schnitzer, Mireille E.; Van der Laan, Mark J.; Moodie, Erica E. M.; Platt, Robert W.: Effect of breastfeeding on gastrointestinal infection in infants: a targeted maximum likelihood approach for clustered longitudinal data (2014)
  15. Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)
  16. Sexton, Joseph; Laake, Petter: Boosted coefficient models (2012)
  17. Ulla Mogensen; Hemant Ishwaran; Thomas Gerds: Evaluating Random Forests for Survival Analysis Using Prediction Error Curves (2012) not zbMATH
  18. Adler, Werner; Brenning, Alexander; Potapov, Sergej; Schmid, Matthias; Lausen, Berthold: Ensemble classification of paired data (2011)
  19. Adler, Werner; Potapov, Sergej; Lausen, Berthold: Classification of repeated measurements data using tree-based ensemble methods (2011)
  20. Bou-Hamad, Imad; Larocque, Denis; Ben-Ameur, Hatem: A review of survival trees (2011)

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