教与试:一种简单的交互技术,用于最终用户的探索性数据建模

Advait Sarkar, A. Blackwell, M. Jamnik, M. Spott
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引用次数: 12

摘要

现代经济越来越依赖于探索性数据分析。这在很大程度上取决于数据科学家——使用统计工具和编程语言处理数据的专家统计学家。我们的目标是通过简单的交互技术和隐喻,为没有受过统计训练的最终用户提供一些这种分析能力。我们描述了一种基于电子表格的交互技术,可用于构建和应用复杂的统计模型,如神经网络、决策树、支持向量机和线性回归。我们提出的实验结果表明,我们的原型可以被没有统计学或计算专业培训的用户理解并成功应用,并且与系统交互的经验使他们对探索性统计建模背后的概念有了一定的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Teach and try: A simple interaction technique for exploratory data modelling by end users
The modern economy increasingly relies on exploratory data analysis. Much of this is dependent on data scientists - expert statisticians who process data using statistical tools and programming languages. Our goal is to offer some of this analytical power to end-users who have no statistical training through simple interaction techniques and metaphors. We describe a spreadsheet-based interaction technique that can be used to build and apply sophisticated statistical models such as neural networks, decision trees, support vector machines and linear regression. We present the results of an experiment demonstrating that our prototype can be understood and successfully applied by users having no professional training in statistics or computing, and that the experience of interacting with the system leads them to acquire some understanding of the concepts underlying exploratory statistical modelling.
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