Ensembles of dipolar trees for prediction of survival time

• Autorzy: Krętowska M.
• Języki publikacji: EN

Abstrakty

EN

In the paper, the application of random forest for prediction of survival time is presented. The observed data loss function is based on inverse probability of censoring weights. The random forest consists of the sequence of multivariate regression trees created on the base of the learning sets, randomly generated from the given dataset. The applied regression trees use minimization of dipolar criterion function for finding the splits in the internal nodes.

Słowa kluczowe

EN

survival analysis; random forest; dipolar criterion function

PL

analiza przeżycia; lasy losowe; prognozowanie

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2007
• Tom: Vol. 27, no. 3
• Strony: 67--75
• Opis fizyczny: Bibliogr. 14 poz., wykr.

Twórcy

autor

Krętowska M.

• Białystok Technical University, Faculty of Computer Science, Wiejska 45a, Białystok, Poland,

Bibliografia

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