Statistical Analysis and Data Mining
Journal Title
- Statistical Analysis and Data Mining
ISSN
- E 1932-1864 | P 1932-1872 | 1932-1872 | 1932-1864
Publisher
- Wiley Subscription Services
- Wiley-Blackwell
Listed on(Coverage)
| JCR | 2015-2019 |
|---|---|
| SJR | 2009-2019 |
| CiteScore | 2011-2019 |
| SCIE | 2015-2021 |
| CC | 2016-2021 |
| SCOPUS | 2017-2020 |
Active
- Active
based on the information
- SCOPUS:2020-10
Country
- USA
Aime & Scopes
- Statistical Analysis and Data Mining addresses the broad area of data analysis, including data mining algorithms, statistical approaches, and practical applications. Topics include problems involving massive and complex datasets, solutions utilizing innovative data mining algorithms and/or novel statistical approaches, and the objective evaluation of analyses and solutions. Of special interest are articles that describe 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 /// Are application and solution oriented with a focus on solving real problems /// Describe innovative data mining algorithms or novel statistical approaches /// Compare and contrast techniques to solve a problem, along with an objective evaluation of the analyses and the solutions The goals of this interdisciplinary journal are to encourage collaborations across disciplines, communication of novel data mining and statistical techniques to both novices and experts involved in the analysis of data from practical problems, and a principled evaluation of analyses and solutions. The 21st Century has become a Century of Data, with most domains striving for useful general models for their mountains of data. Data mining and statistical analysis are amongst the most effective bodies of methodology and technology capable of producing useful general models from massive, complex datasets.