Add to ORKGAbstract Subgroup discovery is a data mining technique which extracts interesting rules with respect to a target variable. An important characteristic of this task is the combination of predictive and descriptive induction. An overview related to the task of subgroup discov-ery is presented. This review focuses on the foundations, algorithms, and advanced studies together with the applications of subgroup discovery presented throughout the specialised bibliography
Subgroup discovery consists in finding subsets of individuals from a given population which have dis...
Rule learning is typically used in solving classification and prediction tasks. However, learning of...
Subgroup discovery is the task of identifying subgroups that show the most unusual statistical (dist...
Subgroup discovery is a data mining technique which extracts interesting rules with respect to a ta...
local exceptionality detection, interestingness measures, algorithms, exploratory data mining Subgro...
The discovery of (interesting) subgroups has a high practical relevance in all domains of science or...
Large volumes of data are collected today in many domains. Often, there is so much data available, t...
This dissertation investigates how to adapt standard classification rule learning approaches to su...
Subgroup discovery is a data mining technique which focuses fascinating rules regarding a target var...
Abstract. We propose an approach to subgroup discovery using distri-bution rules (a kind of associat...
This paper presents an approach to expert-guided subgroup discovery. The main step of the subgroup d...
Large volumes of data are collected today in many domains. Often, there is so much data available, t...
I Subgroup Discovery (SD) algorithms aim to find subgroups of data (represented by rules) that are s...
Abstract. This paper presents a subgroup discovery algorithm APRIORI-SD, developed by adapting assoc...
Large data is challenging for most existing discovery algorithms, for several reasons. First of all,...
Subgroup discovery consists in finding subsets of individuals from a given population which have dis...
Rule learning is typically used in solving classification and prediction tasks. However, learning of...
Subgroup discovery is the task of identifying subgroups that show the most unusual statistical (dist...
Subgroup discovery is a data mining technique which extracts interesting rules with respect to a ta...
local exceptionality detection, interestingness measures, algorithms, exploratory data mining Subgro...
The discovery of (interesting) subgroups has a high practical relevance in all domains of science or...
Large volumes of data are collected today in many domains. Often, there is so much data available, t...
This dissertation investigates how to adapt standard classification rule learning approaches to su...
Subgroup discovery is a data mining technique which focuses fascinating rules regarding a target var...
Abstract. We propose an approach to subgroup discovery using distri-bution rules (a kind of associat...
This paper presents an approach to expert-guided subgroup discovery. The main step of the subgroup d...
Large volumes of data are collected today in many domains. Often, there is so much data available, t...
I Subgroup Discovery (SD) algorithms aim to find subgroups of data (represented by rules) that are s...
Abstract. This paper presents a subgroup discovery algorithm APRIORI-SD, developed by adapting assoc...
Large data is challenging for most existing discovery algorithms, for several reasons. First of all,...
Subgroup discovery consists in finding subsets of individuals from a given population which have dis...
Rule learning is typically used in solving classification and prediction tasks. However, learning of...
Subgroup discovery is the task of identifying subgroups that show the most unusual statistical (dist...