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Topological Properties of Measurable Structures and Sufficient Conditions for Uniform Convergence of Frequencies to Probabilities

机译:可测结构的拓扑性质和频率均匀收敛到概率的充分条件

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摘要

The event-uniform convergence of frequencies to probabilities is one of the main tools of the today theory of learning pattern recognition which enables one to substantiate the generalizability of the learning algorithms. Proposed was a new approach to derivation of the sufficient conditions for such convergence on the basis of only the topological properties of the event σ-algebra induced by the class under consideration.
机译:频率到概率的事件统一收敛是当今学习模式识别理论的主要工具之一,它使人们能够证实学习算法的一般性。提出了一种仅基于所考虑的类所引起的事件σ代数的拓扑特性来推导此类收敛的充分条件的新方法。

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