The Importance of Knowing When to Stop
نویسنده
چکیده
Objectives: Component-wise boosting algorithms have evolved into a popular estimation scheme in biomedical regression settings. The iteration number of these algorithms is the most important tuning parameter to optimize their performance. To date, no fully automated strategy for determining the optimal stopping iteration of boosting algorithms has been proposed. Methods: We propose a fully data-driven sequential stopping rule for boosting algorithms. It combines resampling methods with
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The development and evolution of any system–person, organization–nation depends on how the system succeeds to bridge the gap between what the system knows and what the system does (with the knowledge). We call this the gap between knowing and doing or the knowing-doing gap. If the system does not do what it knows, it will lose out in competition with other systems, its relative performance in...
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