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Cited by 308

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Unbiased split selection for classification trees based on the Gini Index

Open access
Strobl, Carolin, Boulesteix, Anne-Laure, Augustin, Thomas·2007·Computational Statistics & Data Analysis
DOI 10.1016/j.csda.2006.12.030
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Cites

Research works printed but not linked: 16

  1. Benjamini, 1995, Controlling the false discovery rate: a practical and powerful approach to multiple testing, J. Roy. Statist. Soc. B, 57, 289, 10.1111/j.2517-6161.1995.tb02031.x · DOI · Paper page
  2. Boulesteix, 2006, Maximally selected chi-square statistics and binary splits of nominal variables, Biometrical J., 48, 838, 10.1002/bimj.200510191 · doi:10.1002/bimj.200510191
  3. Boulesteix, 2006, Maximally selected chi-square statistics for ordinal variables, Biometrical J., 48, 451, 10.1002/bimj.200510161 · doi:10.1002/bimj.200510161
  4. Boulesteix, 2006, Identification of interaction patterns and classification with applications to microarray data, Comput. Statist. Data Anal., 50, 783, 10.1016/j.csda.2004.10.004 · doi:10.1016/j.csda.2004.10.004
  5. Breiman, 2001, Random forests, Mach. Learn., 45, 5, 10.1023/A:1010933404324 · DOI · Paper page
  6. Kim, 2001, Classification trees with unbiased multiway splits, J. Amer. Statist. Assoc., 96, 589, 10.1198/016214501753168271 · DOI · Paper page
  7. Koziol, 1991, On maximally selected chi-square statistics, Biometrics, 47, 1557, 10.2307/2532406 · DOI
  8. Loh, 2002, Regression trees with unbiased variable selection and interaction detection, Statist. Sinica, 12, 361
  9. Loh, 1997, Split selection methods for classification trees, Statist. Sinica, 7, 815
  10. Miller, 1982, Maximally selected Chi square statistics, Biometrics, 38, 1011, 10.2307/2529881 · DOI · Paper page
  11. Schmaußer, M., 2005. Auswirkungen verschiedener Stoffwechsellagen auf die Fertilität beim Milchrind unter besonderer Berücksichtigung der individuellen Futteraufnahme und unter Berücksichtigung verschiedener Melksysteme. Ph.D. Thesis, Faculty of Veterinary Medicine, University of Munich LMU, Munich, Germany.
  12. Shih, 2004, A note on split selection bias in classification trees, Comput. Statist. Data Anal., 45, 457, 10.1016/S0167-9473(03)00064-1 · DOI
  13. Shih, 2004, Variable selection bias in regression trees with constant fits, Comput. Statist. Data Anal., 45, 595, 10.1016/S0167-9473(03)00036-7 · DOI
  14. Strobl, C., 2005. Variable selection in classification trees based on imprecise probabilities. In: Cozman, F., Nau, R., Seidenfeld, T. (Eds.), Proceedings of the Fourth International Symposium on Imprecise Probabilities and their Applications, Carnegy Mellon University, Pittsburgh, PA, USA, SIPTA, Manno, pp. 340–348.
  15. Strobl, C., Boulesteix, A.-L., Zeileis, A., Hothorn, T., 2006. Bias in random forest variable importance measures: illustrations, sources and a solution. BMC Bioinformatics, accepted for publication. · DOI · Paper page
  16. White, 1994, Bias in information based measures in decision tree induction, Mach. Learn., 15, 321, 10.1007/BF00993349 · DOI · Paper page

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Metadata

Authors
Strobl, C., Boulesteix, A.-L., & Augustin, T.
Venue
Computational Statistics & Data Analysis
Publisher
Elsevier BV
Published
2007-09
Volume
52
Issue
1
Pages
483-501
ISSN
0167-9473 (ISSN-L)
DOI
10.1016/j.csda.2006.12.030
OpenAlex
W2110878112
Cited by
308
References
3
FWCI
24.93
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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