The following work is a preprint collection of formal proofs regarding the convergence properties of the AdaBoost machine learning algorithm's classifier and margins. Various math and computer science papers have been written regarding conjectures and special cases of these convergence properties. Furthermore, the margins of AdaBoost feature prominently in the research surrounding the algorithm. At the zenith of this paper we present how AdaBoost's classifier and margins converge on a value that agrees with decades of research. After this, we show how various quantities associated with the combined classifier converge.

翻译：以下工作是一份预印本合集，其中包含关于AdaBoost机器学习算法的分类器及其间隔收敛性的形式化证明。各种数学和计算机科学论文已针对这些收敛性质的猜想及特例进行了探讨。此外，AdaBoost的间隔在该算法相关研究中占据重要地位。本文的核心成果是展示了AdaBoost的分类器及其间隔如何收敛到一个与数十年研究相一致的数值。随后，我们进一步证明了与组合分类器相关的各种量的收敛性。