Subjectively interesting subgroup discovery on real-valued targets

Jefrey Lijffijt; Bo Kang; W. Duivesteijn; Kai Puolamäki; Emilia Oikarinen; Tijl de Bie

doi:10.1109/ICDE.2018.00148

Subjectively interesting subgroup discovery on real-valued targets

Jefrey Lijffijt, Bo Kang, W. Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl de Bie

Data Mining

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

5 Citations (Scopus)

Abstract

Deriving insights from high-dimensional data is one of the core problems in data mining. The difficulty mainly stems from the large number of variable combinations to potentially consider. Hence, an obvious question is whether we can automate the search for interesting patterns. Here, we consider the setting where a user wants to learn as efficiently as possible about real-valued attributes. We introduce a method to find subgroups in the data that are maximally informative (in the Information Theoretic sense) with respect to one or more real-valued target attributes. The succinct subgroup descriptions are in terms of arbitrarily-typed description attributes. The approach is based on the Subjective Interestingness framework FORSIED to use prior knowledge when mining most informative patterns.

Original language	English
Title of host publication	Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018)
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	1352-1355
Number of pages	4
ISBN (Electronic)	978-1-5386-5520-7
ISBN (Print)	978-1-5386-5521-4
DOIs	https://doi.org/10.1109/ICDE.2018.00148
Publication status	Published - 24 Oct 2018
Event	2018 IEEE 34th International Conference on Data Engineering (ICDE) - Paris, France Duration: 16 Apr 2018 → 19 Apr 2018

Conference

Conference	2018 IEEE 34th International Conference on Data Engineering (ICDE)
Country/Territory	France
City	Paris
Period	16/04/18 → 19/04/18

Keywords

Exceptional Model Mining
Exploratory Data Mining
Pattern Mining
Subgroup Discovery
Subjective Interestingness

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10.1109/ICDE.2018.00148

Cite this

Lijffijt, J., Kang, B., Duivesteijn, W., Puolamäki, K., Oikarinen, E., & de Bie, T. (2018). Subjectively interesting subgroup discovery on real-valued targets. In Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018) (pp. 1352-1355). Article 8509369 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICDE.2018.00148

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keywords = "Exceptional Model Mining, Exploratory Data Mining, Pattern Mining, Subgroup Discovery, Subjective Interestingness",

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doi = "10.1109/ICDE.2018.00148",

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Lijffijt, J, Kang, B, Duivesteijn, W, Puolamäki, K, Oikarinen, E & de Bie, T 2018, Subjectively interesting subgroup discovery on real-valued targets. in Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018)., 8509369, Institute of Electrical and Electronics Engineers, Piscataway, pp. 1352-1355, 2018 IEEE 34th International Conference on Data Engineering (ICDE), Paris, France, 16/04/18. https://doi.org/10.1109/ICDE.2018.00148

Subjectively interesting subgroup discovery on real-valued targets. / Lijffijt, Jefrey; Kang, Bo; Duivesteijn, W. et al.
Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018). Piscataway: Institute of Electrical and Electronics Engineers, 2018. p. 1352-1355 8509369.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Subjectively interesting subgroup discovery on real-valued targets

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