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In the paper the possibilities of assessing the variable influence on the failure occurrence is shown. Ensemble of dipolar survival trees is used as a prediction tool. The technique is able to cope with censored data (data with incomplete observations) as well as with competing risks data. The results are presented on the base of two real datasets for which the influence of discrete and continuous...
Wpracy przedstawiona została analiza porównawcza własności prognostycznych komitetów bazujących na sieciach neuronowych oraz drzewach regresyjnych. Tworzenie kolejnych się przestrzeni cech w obu metodach polega na minimalizacji odpowiednio skonstruowanego kryterium dipolowego. Do porównania metod wykorzystano indeks Brier’a oraz pośrednią i bezpośrednią miarę jakości predykcji. Eksperymenty wykonane...
W pracy bezwzględny błąd predykcji jest wykorzystywany do oceny jakości prognostycznej poszczególnych cech. Narzędzie prognostyczne - lasy losowe - jest konstruowane w celu uzyskania estymatora funkcji przeżycia. Jest on następnie porównywany z estymatorem funkcji przeżycia Kaplana-Meiera, utworzonym przy założeniu jednorodności populacji. Elementem składowym lasów są dipolowe drzewa przeżycia. Zastosowanie...
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...
In this paper a new method for induction of multivariate regression trees is presented. The technique is designed for the survival time prediction and based on given data. The proposed method aims at identification of subgroups of patients with homogenous survival experience i.e. homogenous response for a given treatment. The method allows using information from censored cases for which the exact...
The procedure of designing the non-linear dependencies of survival time on a family of covariates is described in the paper. This dependence is treated as a prognostic model. The first stage of this procedure involves designing such layers of formal neurons which are ranked with respect to selected subsets of censored data. The model based on the hierarchical networks of formal neurons results in...
Statistical methods which are usually applied in survival data analysis often require some prior assumptions on the studied phenomena. In the case of the Iack of such knowledge other techniques have been proposed. Among them neural networks have been recently pointed out to be a very promising tool to cope with survival data. In the paper we consider a modular neural network applied to the grouped...
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