{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T03:50:14Z","timestamp":1773028214760,"version":"3.50.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2019,10,29]],"date-time":"2019-10-29T00:00:00Z","timestamp":1572307200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,10,29]],"date-time":"2019-10-29T00:00:00Z","timestamp":1572307200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"National Science Foundation","award":["163310"],"award-info":[{"award-number":["163310"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Comput Stat"],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s00180-019-00929-4","type":"journal-article","created":{"date-parts":[[2019,10,30]],"date-time":"2019-10-30T22:51:43Z","timestamp":1572475903000},"page":"983-999","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Random forest with acceptance\u2013rejection trees"],"prefix":"10.1007","volume":"35","author":[{"given":"Peter","family":"Calhoun","sequence":"first","affiliation":[]},{"given":"Melodie J.","family":"Hallett","sequence":"additional","affiliation":[]},{"given":"Xiaogang","family":"Su","sequence":"additional","affiliation":[]},{"given":"Guy","family":"Cafri","sequence":"additional","affiliation":[]},{"given":"Richard A.","family":"Levine","sequence":"additional","affiliation":[]},{"given":"Juanjuan","family":"Fan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,29]]},"reference":[{"key":"929_CR1","first-page":"113","volume":"1","author":"E Allwein","year":"2000","unstructured":"Allwein E, Schapire R, Singer Y (2000) Reducing multiclass to binary: a unifying approach for margin classifiers. J Mach Learn Res 1:113\u2013141","journal-title":"J Mach Learn Res"},{"key":"929_CR2","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1162\/neco.1997.9.7.1545","volume":"9","author":"Y Amit","year":"1997","unstructured":"Amit Y, Geman D (1997) Shape quantization and recognition with randomized trees. Neural Comput 9:1545\u20131588","journal-title":"Neural Comput"},{"key":"929_CR3","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman L (1996) Bagging predictors. Mach Learn 24:123\u2013140","journal-title":"Mach Learn"},{"key":"929_CR4","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45:5\u201332","journal-title":"Mach Learn"},{"key":"929_CR5","unstructured":"Breiman L (2004) Consistency for a simply model of random forests. Technical report, University of California at Berkeley"},{"key":"929_CR6","doi-asserted-by":"crossref","unstructured":"Caruana R, Niculescu-Mizil A (2006) An empirical comparison of supervised learning algorithms. In: Proceedings of the 23rd international conference on machine learning, pp 161\u2013168","DOI":"10.1145\/1143844.1143865"},{"key":"929_CR7","doi-asserted-by":"crossref","unstructured":"Caruana R, Karampatziakis N, Yessenalina A (2008) An empirical evaluation of supervised learning in high dimensions. In: Proceedings of the 25th international conference on machine learning, pp 96\u2013103","DOI":"10.1145\/1390156.1390169"},{"key":"929_CR8","volume-title":"Graphical methods for data analysis","author":"J Chambers","year":"1983","unstructured":"Chambers J, Cleveland W, Kleiner B, Tukey P (1983) Graphical methods for data analysis. Wadsworth, Belmont"},{"key":"929_CR9","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1890\/07-0539.1","volume":"88","author":"D Cutler","year":"2007","unstructured":"Cutler D, Edwards T Jr, Beard K, Cutler A, Hess K, Gibson J, Lawler J (2007) Random forest for classification in ecology. Ecology 88:2783\u20132792","journal-title":"Ecology"},{"key":"929_CR10","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1002\/sim.4780080806","volume":"8","author":"R Davis","year":"1989","unstructured":"Davis R, Anderson Z (1989) Exponential survival trees. Stat Med 8:947\u2013962","journal-title":"Stat Med"},{"key":"929_CR11","first-page":"184","volume":"2","author":"R Derrig","year":"2008","unstructured":"Derrig R, Francis L (2008) Distinguishing the forest from the trees: a comparison of tree-based data mining methods. Variance 2:184\u2013208","journal-title":"Variance"},{"key":"929_CR12","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1613\/jair.105","volume":"2","author":"T Dietterich","year":"1995","unstructured":"Dietterich T, Bakiri G (1995) Solving multiclass learning problems via error\u2013correcting output codes. J Artif Intell Res 2:263\u2013286","journal-title":"J Artif Intell Res"},{"key":"929_CR13","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1198\/016214506000000438","volume":"101","author":"J Fan","year":"2006","unstructured":"Fan J, Su X, Levine R, Nunn M, LeBlanc M (2006) Trees for correlated survival data by goodness of split, with applications to tooth prognosis. J Am Stat Assoc 101:959\u2013967","journal-title":"J Am Stat Assoc"},{"key":"929_CR14","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"J Friedman","year":"2001","unstructured":"Friedman J (2001) Greedy function approximation: the gradient boosting machine. Ann Stat 29:1189\u20131232","journal-title":"Ann Stat"},{"key":"929_CR15","unstructured":"Genuer R, Poggi JM, Tuleau C (2008) Random forests: some methodological insights. arXiv"},{"key":"929_CR16","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","volume":"63","author":"P Geurts","year":"2006","unstructured":"Geurts P, Ernst D, Wehenkel L (2006) Extremely randomized trees. Mach Learn 63:3\u201342","journal-title":"Mach Learn"},{"key":"929_CR17","first-page":"1065","volume":"69","author":"L Gordon","year":"1985","unstructured":"Gordon L, Olshen R (1985) Tree-structured survival analysis. Cancer Treat Rep 69:1065\u20131069","journal-title":"Cancer Treat Rep"},{"key":"929_CR18","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1080\/00949655.2012.741599","volume":"84","author":"A Hajjem","year":"2014","unstructured":"Hajjem A, Bellavance F, Larocque D (2014) Mixed effects random forest for clustered data. J Stat Comput Simul 84:1313\u20131328","journal-title":"J Stat Comput Simul"},{"key":"929_CR19","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1148\/radiology.143.1.7063747","volume":"143","author":"J Hanley","year":"1982","unstructured":"Hanley J, McNeil B (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29\u201336","journal-title":"Radiology"},{"key":"929_CR20","unstructured":"Ho T (1995) Random decision forest. In: Proceedings of the 3rd international conference on document analysis and recognition, vol 1, pp 278\u2013282"},{"key":"929_CR21","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1109\/34.709601","volume":"20","author":"T Ho","year":"1998","unstructured":"Ho T (1998) The random subspace method of constructing decision forests. IEEE Trans Pattern Anal Mach Intell 20:832\u2013844","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"929_CR22","volume-title":"Applied logistic regression","author":"D Hosmer","year":"1989","unstructured":"Hosmer D, Lemeshow S (1989) Applied logistic regression. Wiley, New York"},{"key":"929_CR23","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1198\/106186005X59630","volume":"14","author":"T Hothorn","year":"2005","unstructured":"Hothorn T, Leisch F, Zeileis A, Hornik K (2005) The design and analysis of benchmark experiments. J Comput Graph Stat 14:675\u2013699","journal-title":"J Comput Graph Stat"},{"key":"929_CR24","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s10994-014-5451-2","volume":"99","author":"H Ishwaran","year":"2015","unstructured":"Ishwaran H (2015) The effect of splitting on random forests. Mach Learn 99:75\u2013118","journal-title":"Mach Learn"},{"key":"929_CR25","unstructured":"Ishwaran H, Kogalur UB (2016) Random forests for survival, regression, and classification (RF-SRC). R package version 2.2.0"},{"key":"929_CR26","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1198\/jasa.2009.tm08622","volume":"105","author":"H Ishwaran","year":"2010","unstructured":"Ishwaran H, Kogalur U, Gorodeski E, Minn A, Lauer M (2010) High-dimensional variable selection for survival data. J Am Stat Assoc 105:205\u2013217","journal-title":"J Am Stat Assoc"},{"key":"929_CR27","doi-asserted-by":"crossref","first-page":"5499","DOI":"10.1002\/sim.3069","volume":"26","author":"I K\u00f6nig","year":"2007","unstructured":"K\u00f6nig I, Malley J, Weimar C, Diener HC, Ziegler A (2007) Practical experiences on the necessity of external validation. Stat Med 26:5499\u20135511","journal-title":"Stat Med"},{"key":"929_CR28","unstructured":"Leisch F, Dimitriadou E (2010) mlbench: Machine Learning Benchmark Problems. R package version 2.1-1"},{"issue":"3","key":"929_CR29","first-page":"18","volume":"2","author":"A Liaw","year":"2002","unstructured":"Liaw A, Wiener M (2002) Classification and regression by randomforest. R News 2(3):18\u201322","journal-title":"R News"},{"key":"929_CR30","doi-asserted-by":"crossref","first-page":"74","DOI":"10.3414\/ME00-01-0052","volume":"51","author":"J Malley","year":"2012","unstructured":"Malley J, Kruppa J, Dasgupta A, Malley K, Ziegler A (2012) Probability machines: consistent probability estimation using nonparametric learning machines. Methods Inform in Med 51:74\u201381","journal-title":"Methods Inform in Med"},{"key":"929_CR31","unstructured":"Newman DJ, Hettich S, Blake CL, Merz CJ (1998) UCI repository of machine learning. \nhttp:\/\/www.ics.uci.edu\/~mlearn\/MLRepository.html\n\n. Accessed May 2018"},{"key":"929_CR32","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1002\/widm.12","volume":"1","author":"M Segal","year":"2011","unstructured":"Segal M, Xiao Y (2011) Multivariate random forests. WIREs Data Min Knowl Discov 1:80\u201387","journal-title":"WIREs Data Min Knowl Discov"},{"key":"929_CR33","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s10994-011-5258-3","volume":"86","author":"R Sela","year":"2012","unstructured":"Sela R, Simonoff J (2012) RE-EM trees: a data mining approach for longitudinal and clustered data. Mach Learn 86:169\u2013207","journal-title":"Mach Learn"},{"key":"929_CR34","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1093\/aje\/kwt312","volume":"179","author":"A Shah","year":"2014","unstructured":"Shah A, Bartlett J, Carpenter J, Nicholas O, Hemingway H (2014) Comparison of random forest and parametric imputation models for imputing missing data using mice: a caliber study. Am J Epidemiol 179:764\u2013774","journal-title":"Am J Epidemiol"},{"key":"929_CR35","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.csda.2006.12.030","volume":"52","author":"C Strobl","year":"2007","unstructured":"Strobl C, Boulesteix A, Zeileis A, Augustin T (2007a) Unbiased split selection for classification trees based on the gini index. Comput Stat Data Anal 52:483\u2013501","journal-title":"Comput Stat Data Anal"},{"key":"929_CR36","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/1471-2105-8-25","volume":"8","author":"C Strobl","year":"2007","unstructured":"Strobl C, Boulesteix A, Zeileis A, Hothorn T (2007b) Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinform 8:25\u201346","journal-title":"BMC Bioinform"},{"key":"929_CR37","unstructured":"Su X, Kang J, Liu L, Yang Q, Fan J, Levine R (2016) Smooth sigmoid surrogate (SSS): An alternative to greedy search in recursive partitioning. Comput Stat Data Anal Under Rev"},{"key":"929_CR38","doi-asserted-by":"crossref","first-page":"2547","DOI":"10.1002\/sim.7660","volume":"37","author":"X Su","year":"2018","unstructured":"Su X, Pena A, Liu L, Levine R (2018) Random forests of interaction trees for estimating individualized treatment effects in randomized trials. Stat Med 37:2547\u20132560","journal-title":"Stat Med"},{"key":"929_CR39","unstructured":"Torgo L (1999) Inductive learning of tree-based regression models. Ph.D. thesis, University of Porto"},{"key":"929_CR40","first-page":"268","volume":"2","author":"W Yoo","year":"2012","unstructured":"Yoo W, Ference B, Cote M, Schwartz A (2012) A comparison of logistic re gression, logic regression, classification tree, and random forests to identify effective gene\u2013gene and gene\u2013environment interactions. Int J Appl Sci Technol 2:268","journal-title":"Int J Appl Sci Technol"}],"container-title":["Computational Statistics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-019-00929-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00180-019-00929-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-019-00929-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T00:06:27Z","timestamp":1603843587000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00180-019-00929-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,29]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["929"],"URL":"https:\/\/doi.org\/10.1007\/s00180-019-00929-4","relation":{},"ISSN":["0943-4062","1613-9658"],"issn-type":[{"value":"0943-4062","type":"print"},{"value":"1613-9658","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,29]]},"assertion":[{"value":"8 July 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 October 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 October 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}