کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10918825 1090805 2012 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multivariate modeling of complications with data driven variable selection: Guarding against overfitting and effects of data set size
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی تحقیقات سرطان
پیش نمایش صفحه اول مقاله
Multivariate modeling of complications with data driven variable selection: Guarding against overfitting and effects of data set size
چکیده انگلیسی
Despite considerable spread around the optimal number of selected variables, the bootstrapping method is efficient and accurate for sufficiently large data sets, and guards against overfitting for all simulated cases with the exception of some data sets with a particularly low number of events. An appropriate minimum data set size to obtain a model with high predictive power is approximately 200 patients and more than 32 events. With fewer data samples the true predictive power decreases rapidly, and for larger data set sizes the benefit levels off toward an asymptotic maximum predictive power.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Radiotherapy and Oncology - Volume 105, Issue 1, October 2012, Pages 115-121
نویسندگان
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