统计推理范式和统计学习范式

J. Pociecha
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引用次数: 0

摘要

根据统计推断和统计学习的规则进行统计研究的原则之间的异同的出发点是由托马斯·库恩提出的范式理论。在本文的第一部分中,统计推断范式的基本特征被表征,特别注意其在当代统计研究中的局限性。随后,文章提出了本研究面临的挑战,并提出了有效减少挑战的扩大机会。讨论了从数据中学习的本质,定义了统计学习的原理。此外,统计学习范式的显著特征是在统计推断范式和统计学习范式之间的差异的背景下制定的。报告强调,统计学习范式作为讨论的两种范式中比较普遍的一种,扩大了进行统计研究的可能性,特别是在社会经济科学方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The paradigm of statistical inference and the paradigm of statistical learning
The starting point for the presentation of the similarities and differences between the principles of conducting statistical research according to the rules of both statistical inference and statistical learning is the paradigm theory, formulated by Thomas Kuhn. In the first section of this paper, the essential features of the statistical inference paradigm are characterised, with particular attention devoted to its limitations in contemporary statistical research. Subsequently, the article presents the challenges faced by this research jointly with the expanding opportunities for their effective reduction. The essence of learning from data is discussed and the principles of statistical learning are defined. Moreover, significant features of the statistical learning paradigm are formulated in the context of the differences between the statistical inference paradigm and the statistical learning paradigm. It is emphasised that the statistical learning paradigm, as the more universal one of the two discussed, broadens the possibilities of conducting statistical research, especially in socio-economic sciences.
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