Subgroup discovery is a broadly applicable descriptive data mining technique for identifying
interesting subgroups according to some property of interest. This article summarizes …

Finding subsets of a dataset that somehow deviate from the norm, ie where something
interesting is going on, is a classical Data Mining task. In traditional local pattern mining …

Subgroup discovery is a key data mining method that aims at identifying descriptions of
subsets of the data that show an interesting distribution with respect to a pre-defined target …

Subgroup discovery (SD) is an exploratory pattern mining paradigm that comes into its own
when dealing with large real-world data, which typically involves many attributes, of a …

Subgroup discovery (SD) is the task of discovering interpretable patterns in the data that
stand out wrt some property of interest. Discovering patterns that accurately discriminate a …

Subgroup discovery is the task of discovering patterns that accurately discriminate a class
label from the others. Existing approaches can uncover such patterns either through an …

The objective of subgroup discovery is to find groups of individuals who are statistically
different from others in a large data set. Most existing measures of the quality of subgroups …

Subgroup-discovery methods allow users to obtain simple descriptions of interesting regions
in a dataset. Using constraints in subgroup discovery can enhance interpretability even …

In this paper, we measure the linear separability of hidden layer outputs to study the
characteristics of deep neural networks. In particular, we first propose Minkowski difference …

Subgroup discovery in labeled data is the task of discovering patterns in the description
space of objects to find subsets of objects whose labels show an interesting distribution, for …