The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Multiple additive regression trees with application in epidemiology
Abstract
Predicting future outcomes based on knowledge obtained from past observational data is a common application in a wide variety of areas of scientific research. In the present paper, prediction will be focused on various grades of cervical preneoplasia and neoplasia. Statistical tools used for prediction should of course possess predictive accuracy, and preferably meet secondary requirements such as speed, ease of use, and interpretability of the resulting predictive model. A new automated procedure based on an extension (called ‘boosting’) of regression and classification tree (CART) models is described. The resulting tool is a fast ‘off‐the‐shelf’ procedure for classification and regression that is competitive in accuracy with more customized approaches, while being fairly automatic to use (little tuning), and highly robust especially when applied to less than clean data. Additional tools are presented for interpreting and visualizing the results of such multiple additive regression tree (MART) models. Copyright © 2003 John Wiley & Sons, Ltd.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731
Self-citationClassification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 20,825
Self-citationClassification and regression trees
Praagman, J. (1985) · European Journal of Operational Research · doi:10.1016/0377-2217(85)90321-2 · Cited by 10,053
Friedman, J., Hastie, T., & Tibshirani, R. (2000) · The Annals of Statistics · doi:10.1214/aos/1016218223 · Cited by 6,884
Self-citationCART: Classification and Regression Trees
(2009) · The Top Ten Algorithms in Data Mining · doi:10.1201/9781420089653-17 · Cited by 163
(1996)
Cited by
A working guide to boosted regression trees
Elith, J., Leathwick, J. R., & Hastie, T. (2008) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2008.01390.x · Cited by 6,484
Ridker, P. M., Buring, J. E., Rifai, N., & Cook, N. R. (2007) · JAMA · doi:10.1001/jama.297.6.611 · Cited by 1,814
Zhang, Y., Chen, H. Y. H., & Reich, P. B. (2012) · Journal of Ecology · doi:10.1111/j.1365-2745.2011.01944.x · Cited by 799
Error and uncertainty in habitat models
BARRY, S., & ELITH, J. (2006) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2006.01136.x · Cited by 657
Leathwick, J. R., Elith, J., & Hastie, T. (2006) · Ecological Modelling · doi:10.1016/j.ecolmodel.2006.05.022 · Cited by 451
Metadata
- Authors
- Friedman, J. H., & Meulman, J. J.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2003-04-14
- Volume
- 22
- Issue
- 9
- Pages
- 1365-1381
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2125223451
- Cited by
- 786
- References
- 6
- FWCI
- 2.61
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Multiple additive regression trees with application in epidemiology. https://app.cochat.ai/papers/10.1002/sim.1501
- The paper
- Friedman, J. H., & Meulman, J. J. (2003). Multiple additive regression trees with application in epidemiology. Statistics in Medicine. https://doi.org/10.1002/sim.1501
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
