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:: Volume 24, Issue 1 (9-2019) ::
Andishe 2019, 24(1): 33-42 Back to browse issues page
Survival Analysis using Bayesian Additive RegressionTrees
Fatemeh Hosseini Dr *, Omid Karimi Dr, Fatemeh Hamedi Miss
Faculty of Mathematics, Statistics and Computer, Department of Statistics
Abstract:   (796 Views)
‎Tree models represent a new and innovative way of analyzing large data sets by dividing predictor space into simpler areas‎. ‎Bayesian Additive Regression Trees model‎, ‎a model that we explain in this article‎, ‎uses a totality of trees in its structure‎, ‎since the combination of several trees from a tree only has a higher accuracy‎.

‎Then‎, ‎this model is a tree-based model and a nonparametric model that uses general aggregation methods‎, ‎and boosting algorithms in particular and in fact is extension of the classification and Regression Tree methods in which the decision tree exists in the structure of these methods‎.

‎In this method‎, ‎on the parameters of the model sum of tree and put regular prior then use the boosting algorithms for analysis‎. ‎In this paper‎, ‎first the Bayesian Additive Regression Trees model is introduced and then applied in survival analysis of lung cancer patients‎.

Keywords: ‎Tree Models‎, ‎Bayesian Additive Model‎, ‎Decision Tree‎.
Full-Text [PDF 1328 kb]   (177 Downloads)    
Type of Study: Research | Subject: Special
Received: 2019/01/8 | Accepted: 2019/09/21 | Published: 2019/10/22
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Hosseini F, Karimi O, Hamedi F. Survival Analysis using Bayesian Additive RegressionTrees. Andishe. 2019; 24 (1) :33-42
URL: http://andisheyeamari.irstat.ir/article-1-747-en.html


Volume 24, Issue 1 (9-2019) Back to browse issues page
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