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Exceptionally monotone models : the rank correlation model class for exceptional model mining

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Abstract
Exceptional Model Mining strives to find coherent subgroups of the dataset where multiple target attributes interact in an unusual way. One instance of such an investigated form of interaction is Pearson's correlation coefficient between two targets. EMM then finds subgroups with an exceptionally linear relation between the targets. In this paper, we enrich the EMM toolbox by developing the more general rank correlation model class. We find subgroups with an exceptionally monotone relation between the targets. Apart from catering for this richer set of relations, the rank correlation model class does not necessarily require the assumption of target normality, which is implicitly invoked in the Pearson's correlation model class. Furthermore, it is less sensitive to outliers.
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Chicago
Downar, Lennart, and Wouter Duivesteijn. 2015. “Exceptionally Monotone Models : the Rank Correlation Model Class for Exceptional Model Mining.” In 2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), 111–120. Nov 14-17, 2015.
APA
Downar, L., & Duivesteijn, W. (2015). Exceptionally monotone models : the rank correlation model class for exceptional model mining. 2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM) (pp. 111–120). Presented at the IEEE International Conference on Data Mining (ICDM), Nov 14-17, 2015.
Vancouver
1.
Downar L, Duivesteijn W. Exceptionally monotone models : the rank correlation model class for exceptional model mining. 2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM). Nov 14-17, 2015; 2015. p. 111–20.
MLA
Downar, Lennart, and Wouter Duivesteijn. “Exceptionally Monotone Models : the Rank Correlation Model Class for Exceptional Model Mining.” 2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM). Nov 14-17, 2015, 2015. 111–120. Print.
@inproceedings{8519651,
  abstract     = {Exceptional Model Mining strives to find coherent subgroups of the dataset where multiple target attributes interact in an unusual way. One instance of such an investigated form of interaction is Pearson's correlation coefficient between two targets. EMM then finds subgroups with an exceptionally linear relation between the targets. In this paper, we enrich the EMM toolbox by developing the more general rank correlation model class. We find subgroups with an exceptionally monotone relation between the targets. Apart from catering for this richer set of relations, the rank correlation model class does not necessarily require the assumption of target normality, which is implicitly invoked in the Pearson's correlation model class. Furthermore, it is less sensitive to outliers.},
  author       = {Downar, Lennart and Duivesteijn, Wouter},
  booktitle    = {2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM)},
  isbn         = {978-1-4673-9503-8},
  issn         = {1550-4786},
  keyword      = {IBCN},
  language     = {eng},
  location     = {Atlantic City, NJ},
  pages        = {111--120},
  title        = {Exceptionally monotone models : the rank correlation model class for exceptional model mining},
  url          = {http://dx.doi.org/10.1109/ICDM.2015.81},
  year         = {2015},
}

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