Statistical Analysis and Data Mining

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 datasetsAre application and solution oriented with a focus on solving real problemsDescribe innovative data mining algorithms or novel statistical approachesCompare and contrast techniques to solve a problem, along with an objective evaluation of the analyses and the solutionsThe 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.Statistical Analysis and Data Mining will be a useful resource to those solving practical problems, at the same time enabling them to benefit from ideas developed in other domains. It will be an international journal, with an interdisciplinary focus, covering areas which are becoming increasingly important, and likely to remain so in the foreseeable future.

Statistical Analysis and Data Mining期刊中文简介

统计分析和数据挖掘涉及数据分析的广泛领域，包括数据挖掘算法、统计方法和实际应用。主题包括涉及大量和复杂数据集的问题，使用创新的数据挖掘算法和/或新的统计方法的解决方案，以及分析和解决方案的客观评价。特别感兴趣的是描述分析技术的文章，并讨论它们在实际问题中的应用，以便科学、工程和商业领域的专家能够访问和受益。该杂志的重点是满足下列一项或多项标准的论文:解决与大量复杂数据集相关的数据分析问题应用程序和解决方案是否以解决实际问题为重点描述创新的数据挖掘算法或新的统计方法比较和对比解决问题的技术，并对分析和解决方案进行客观评价这本跨学科杂志的目标是鼓励跨学科的合作，将新的数据挖掘和统计技术传播给从实际问题中分析数据的新手和专家，并对分析和解决方案进行有原则的评估。21世纪已经成为数据的世纪，大多数领域都在为他们堆积如山的数据寻找有用的通用模型。数据挖掘和统计分析是最有效的方法和技术机构之一，能够从大量复杂的数据集中产生有用的通用模型。统计分析和数据挖掘将是解决实际问题的有用资源，同时使他们能够从其他领域发展的思想中获益。它将是一份跨学科的国际期刊，涵盖了越来越重要的领域，在可预见的未来很可能仍将如此。

中科院SCI期刊分区：Statistical Analysis and Data Mining分区

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数学 4区

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

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