Statistical Analysis and Data Mining

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 datasets
Develop 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.

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1区 SCIE Scopus 数学 4区 COMPUTER SCIENCE ARTIFICIAL INTELLIGENCE 计算机：人工智能 INTERDISCIPLINARY APPLICATIONS 计算机：跨学科应用 STATISTICS & PROBABILITY 统计学与概率论

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