During the years many machine learning methods have been introduced for analyzing survival data. Among these, survival trees are a useful method for defining homogeneous groups according to their survival probability. In this context there are still some unclear points, both related to theoretical and practical issues in model fitting and performance evaluation. The aim of this contribution is to shed light on some of these points.
Recursive Partitioning for Survival Data
Ambra Macis
2022-01-01
Abstract
During the years many machine learning methods have been introduced for analyzing survival data. Among these, survival trees are a useful method for defining homogeneous groups according to their survival probability. In this context there are still some unclear points, both related to theoretical and practical issues in model fitting and performance evaluation. The aim of this contribution is to shed light on some of these points.File in questo prodotto:
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