Comparison of Tree-Based Ensembles in Application to Censored Data

被引：0

作者：

Kretowska, Malgorzata ^{[1
]}

机构：

[1] Bialystok Tech Univ, Fac Comp Sci, PL-15351 Bialystok, Poland

来源：

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING ICAISC 2014, PT I | 2014年 / 8467卷

关键词：

survival tree; ensemble; random forest; censored observation; survival analysis; Brier score; SURVIVAL-DATA; PREDICTION; FORESTS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the paper the comparison of ensemble based methods applied to censored survival data was conducted. Bagging survival trees, dipolar survival tree ensemble and random forest were taken into consideration. The prediction ability was evaluated by the integrated Brier score, the prediction measure developed for survival data. Two real datasets with different percentage of censored observations were examined.

引用

页码：551 / 560

页数：10

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