منابع مشابه
Parametric vs Non - Parametric Generative Models
The contrast is exemplified by the following classification task. Let’s assume that we are given data, X , i.e. the observed variable and we want to determine its class label, Y, the unobserved (target) variable. A generative classifier, such as Naive Bayes, makes use of the joint distribution of X and Y, i.e. P(X ,Y) to perform this inference. While a discriminative classifier, such as a Logis...
متن کاملSupplementary Materials to “Combining parametric, semi-parametric, and non-parametric survival models with stacked survival models”
Section 1 demonstrates the connection between the Brier Score in the absence of censoring versus the inverse probability-of-censoring weighted Brier Score. Section 2 derives the meansquared error decomposition presented in Section 3 of the main paper, and presents illustrations and examples regarding the impact of candidate survival models on performance. In addition, a simple example illustrat...
متن کاملCombining parametric, semi-parametric, and non-parametric survival models with stacked survival models.
For estimating conditional survival functions, non-parametric estimators can be preferred to parametric and semi-parametric estimators due to relaxed assumptions that enable robust estimation. Yet, even when misspecified, parametric and semi-parametric estimators can possess better operating characteristics in small sample sizes due to smaller variance than non-parametric estimators. Fundamenta...
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ژورنال
عنوان ژورنال: Journal of Astrophysics and Astronomy
سال: 2014
ISSN: 0250-6335,0973-7758
DOI: 10.1007/s12036-014-9240-x