pysubgroup: Easy-to-Use Subgroup Discovery in Python
This paper introduces the pysubgroup package for subgroup discovery in Python. Subgroup discovery is a well-established data mining task that aims at identifying describable subsets in the data that show an interesting distribution with respect to a certain target concept. The presented package prov...
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Published in | Machine Learning and Knowledge Discovery in Databases Vol. 11053; pp. 658 - 662 |
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Main Authors | , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2019
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Online Access | Get full text |
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Summary: | This paper introduces the pysubgroup package for subgroup discovery in Python. Subgroup discovery is a well-established data mining task that aims at identifying describable subsets in the data that show an interesting distribution with respect to a certain target concept. The presented package provides an easy-to-use, compact and extensible implementation of state-of-the-art mining algorithms, interestingness measures, and visualizations. Since it builds directly on the established pandas data analysis library—a de-facto standard for data science in Python—it seamlessly integrates into preprocessing and exploratory data analysis steps. Code related to this paper is available at: http://florian.lemmerich.net/pysubgroup. |
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ISBN: | 9783030109967 3030109968 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-030-10997-4_46 |