Statistical Analysis and Data Mining The ASA Data Science Journal

期刊简介：Statistical Analysis and Data Mining addresses the broad area of data analysis, including statistical approaches, machine learning, data mining, and applications. Topics include statistical and computational approaches for analyzing massive and complex datasets, novel statistical and/or machine learning methods and theory, and state-of-the-art applications with high impact. Of special interest are articles that describe innovative analytical techniques, and discuss their application to real problems, in such a way that they are accessible and beneficial to domain experts across science, engineering, and commerce.The focus of the journal is on papers which satisfy one or more of the following criteria:Solve data analysis problems associated with massive, complex datasetsDevelop innovative statistical approaches, machine learning algorithms, or methods integrating ideas across disciplines, e.g., statistics, computer science, electrical engineering, operation research.Formulate and solve high-impact real-world problems which challenge existing paradigms via new statistical and/or computational models Provide survey to prominent research topics.

【译文】统计分析和数据挖掘涵盖了数据分析的广泛领域，包括统计方法、机器学习、数据挖掘及其应用。主题包括分析大规模和复杂数据集的统计和计算方法、新颖的统计和/或机器学习方法与理论，以及具有高影响力的最新应用。特别感兴趣的是描述创新分析技术，并讨论它们如何应用于实际问题的文章，以便让来自科学、工程和商业领域的领域专家都能理解和受益。该期刊的重点是满足以下一个或多个标准的论文：解决与大规模、复杂数据集相关的数据分析问题；开发创新的统计方法、机器学习算法或跨学科整合想法的方法，例如统计学、计算机科学、电气工程、运筹学；通过新的统计和/或计算模型提出和解决挑战现有范例的高影响力现实世界问题；对突出研究主题进行综述。