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
References in zbMATH (referenced in 11 articles )
Showing results 1 to 11 of 11.
- Conversano, Claudio; Dusseldorp, Elise: Modeling threshold interaction effects through the logistic classification trunk (2017)
- Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jakob; Studerus, Erich; Casalicchio, Giuseppe; Jones, Zachary M.: Mlr: machine learning in $\bold R$ (2016)
- Cichosz, Paweł: Data mining algorithms. Explained using R (2015)
- Zhou, Yan; McArdle, John J.: Rationale and applications of survival tree and survival ensemble methods (2015)
- Schnitzer, Mireille E.; 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)
- Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)
- Sexton, Joseph; Laake, Petter: Boosted coefficient models (2012)
- Adler, Werner; Potapov, Sergej; Lausen, Berthold: Classification of repeated measurements data using tree-based ensemble methods (2011)
- Bou-Hamad, Imad; Larocque, Denis; Ben-Ameur, Hatem: A review of survival trees (2011)
- Siroky, David S.: Navigating random forests and related advances in algorithmic modeling (2009)
- Hothorn, Torsten; Lausen, Berthold: Double-bagging: Combining classifiers by bootstrap aggregation (2003)