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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.

Journal Home:  Journal Homepage
Editor-in-Chief:   Bertrand Clarke

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.

Print ISSN:

Print ISSN:  19321864,

Electronic ISSN:  19321872

Abstracting and Indexing:  Scopus
Imapct Factor :  
Subject Area and Category:   Computer Science Computer Science Applications Information Systems Mathematics Analysis
Publication Frequency:  
H Index:  33
Best Quartile:


Q2:  Information Systems



Journal Home:  Journal Homepage
Cite Score:  2.5
SNIP:  0.981
Journal Rank(SJR):  0.381
Publisher & Country:

Publisher:  John Wiley and Sons Inc.

Country:  United States