Explicit Contrast Patterns Versus Minimal Jumping Emerging Patterns for Lazy Classification in High Dimensional Data

Marzena Kryszkiewicz , Przemysław Podsiadły


Minimal jumping emerging patterns have been proved very useful for classification purposes. Nevertheless, the determination of minimal jumping emerging patterns may require evaluation of candidate patterns, the number of which might be exponential with respect to the dimensionality of a data set. This property may disallow classification by means of minimal jumping emerging patterns in the case of high dimensional data. In this paper, we derive an upper bound on the lengths of minimal jumping emerging patterns and an upper bound on their number. We also propose an alternative approach to lazy classification which uses explicit contrast patterns instead of minimal jumping emerging patterns, but produces the same classification quality as a lazy classifier based on minimal jumping emerging patterns. We argue that our approach, unlike the approach based on minimal jumping emerging patterns, can be applied in the case of high dimensional data.
Author Marzena Kryszkiewicz (FEIT / IN)
Marzena Kryszkiewicz,,
- The Institute of Computer Science
, Przemysław Podsiadły (FEIT / IN)
Przemysław Podsiadły,,
- The Institute of Computer Science
Publication size in sheets0.7
Book Fujita Hamido, Ali Moonis, Selamat Ali, Sasaki Jun, Kurematsu Masaki (eds.): Trends in Applied Knowledge-Based Systems and Data Science. 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings, Lecture Notes In Computer Science, vol. 9799, 2016, Springer International Publishing, ISBN 978-3-319-42006-6, [978-3-319-42007-3], 1020 p., DOI:10.1007/978-3-319-42007-3
URL http://link.springer.com/chapter/10.1007/978-3-319-42007-3_8
ProjectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 18-05-2015, end date 30-11-2016, II/2015/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 16-10-2020, BookChapterSeriesAndMatConfByConferenceseries
Ministerial score (2013-2016) = 15.0, 16-10-2020, BookChapterSeriesAndMatConfByConferenceseries
Publication indicators WoS Citations = 0; Scopus Citations = 0
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