References in zbMATH (referenced in 16 articles )

Showing results 1 to 16 of 16.
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  1. Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jakob; Studerus, Erich; Casalicchio, Giuseppe; Jones, Zachary M.: Mlr: machine learning in $\bold R$ (2016)
  2. Fitzpatrick, Trevor; Mues, Christophe: An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market (2016)
  3. Teisseyre, Paweł; Kłopotek, Robert A.; Mielniczuk, Jan: Random subspace method for high-dimensional regression with the R package regRSM (2016)
  4. Bertsimas, Dimitris; Brynjolfsson, Erik; Reichman, Shachar; Silberholz, John: OR forum: Tenure analytics: models for predicting research impact (2015)
  5. Fernandez-Lozano, Carlos; Cuiñas, Rubén F.; Seoane, José A.; Fernández-Blanco, Enrique; Dorado, Julian; Munteanu, Cristian R.: Classification of signaling proteins based on molecular star graph descriptors using machine learning models (2015)
  6. Ryan, Kenneth Joseph; Culp, Mark Vere: On semi-supervised linear regression in covariate shift problems (2015)
  7. Arratia, Argimiro: Computational finance. An introductory course with R (2014)
  8. Fernández-Delgado, Manuel; Cernadas, Eva; Barro, Senén; Amorim, Dinani: Do we need hundreds of classifiers to solve real world classification problems? (2014)
  9. Shah, Jasmit; Datta, Somnath; Datta, Susmita: A multi-loss super regression learner (MSRL) with application to survival prediction using proteomics (2014)
  10. Weihs, Claus; Mersmann, Olaf; Ligges, Uwe: Foundations of statistical algorithms. With references to R packages (2014)
  11. Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)
  12. LeDell, Erin; Prabhat; Zubarev, Dmitry Yu.; Austin, Brian; Lester, William A. jun.: Classification of nodal pockets in many-electron wave functions via machine learning (2012)
  13. Netzer, Michael; Kugler, Karl G.; Müller, Laurin A.J.; Weinberger, Klaus M.; Graber, Armin; Baumgartner, Christian; Dehmer, Matthias: A network-based feature selection approach to identify metabolic signatures in disease (2012)
  14. Piccolo, Stephen R.; Frey, Lewis J.: ML-flex: a flexible toolbox for performing classification analyses in parallel (2012)
  15. Williams, Graham: Data Mining with Rattle and R. The art of excavating data for knowledge discovery. (2011)
  16. Bjornson, Robert D.; Carriero, Nicholas J.; Schultz, Martin H.; Shields, Patrick M.; Weston, Stephen B.: NetWorkSpace: A coordination system for high-productivity environments (2009)