Matminer: An open source toolkit for materials data mining
Matminer: An open source toolkit for materials data mining
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DOI：
10.1016/j.commatsci.2018.05.018
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发表时间：
2018-09-01
影响因子：
3.3
通讯作者：
Jain, Anubhav
中科院分区：
文献类型：
--
作者：
Ward, Logan;Dunn, Alexander;Jain, Anubhav
随着材料数据集的规模和范围的增长，数据挖掘和统计学习方法在分析这些材料数据集和构建预测模型方面的作用变得越来越重要。这篇手稿介绍了matminer，一个开源的，基于Python的软件平台，以促进数据驱动的方法分析和预测材料性能。Matminer提供了从外部数据库检索大型数据集的模块，如Materials Project，Citrination，Materials Data Facility和Materials Platform for Data Science。它还为材料社区开发的广泛的特征提取例程库提供了实现，其中有47个特征化类，可以生成数千个单独的描述符，并将它们联合收割机组合成数学函数。最后，matminer提供了一个可视化模块，用于生成交互式的、可共享的图。这些函数的设计方式与Python数据科学社区已经开发和使用的机器学习和数据分析包紧密集成。我们解释了matminer的结构和逻辑，提供了它的各个模块的描述，并展示了几个例子，如何matminer可以用来收集数据，重现文献中报道的数据挖掘研究，并测试新的方法。
As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source, Python-based software platform to facilitate data-driven methods of analyzing and predicting materials properties. Matminer provides modules for retrieving large data sets from external databases such as the Materials Project, Citrination, Materials Data Facility, and Materials Platform for Data Science. It also provides implementations for an extensive library of feature extraction routines developed by the materials community, with 47 featurization classes that can generate thousands of individual descriptors and combine them into mathematical functions. Finally, matminer provides a visualization module for producing interactive, shareable plots. These functions are designed in a way that integrates closely with machine learning and data analysis packages already developed and in use by the Python data science community. We explain the structure and logic of matminer, provide a description of its various modules, and showcase several examples of how matminer can be used to collect data, reproduce data mining studies reported in the literature, and test new methodologies.