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Contrasting Subgroup Discovery

L. Langohr, V. Podpecan, M. Petek, I. Mozetic, K. Gruden, N. Lavrac, H. Toivonen
2012 Computer journal  
To find such subgroups, we propose an approach that consists of two subgroup discovery steps and an intermediate, contrast set definition step.  ...  Subgroup discovery methods find interesting subsets of objects of a given class. Motivated by an application in bioinformatics, we first define a generalized subgroup discovery problem.  ...  Contrasting Subgroup Discovery 7 Hence, some of the subgroups found by the contrasting subgroup discovery were already found by the classical subgroup discovery (for example, education ∧ city).  ... 
doi:10.1093/comjnl/bxs132 fatcat:btjxrfhgjffjrl7pkcg5jrufnu

CSM-SD: Methodology for contrast set mining through subgroup discovery

Petra Kralj Novak, Nada Lavrač, Dragan Gamberger, Antonija Krstačić
2009 Journal of Biomedical Informatics  
As a methodological novelty, it is shown that this task can be effectively solved by transforming it to a more common and well-understood subgroup discovery task.  ...  This paper addresses a data analysis task, known as contrast set mining, whose goal is to find differences between contrasting groups.  ...  Table 2 2 Synonyms for terms used in contrast set mining and subgroup discovery Contrast set mining (CSM) Subgroup discovery (SD) Rule learning (RL) Contrast set Subgroup description Rule conditions  ... 
doi:10.1016/j.jbi.2008.08.007 pmid:18782633 fatcat:63szynaqh5et3izmgamretrafi

Contrast Set Mining Through Subgroup Discovery Applied to Brain Ischaemina Data [chapter]

Petra Kralj, Nada Lavrač, Dragan Gamberger, Antonija Krstačić
Advances in Knowledge Discovery and Data Mining  
The proposed approach to contrast set mining through subgroup discovery was successfully applied to the analysis of records of patients with brain stroke (confirmed by a positive CT test), in contrast  ...  This paper shows that a contrast set mining task can be transformed to a subgroup discovery task whose goal is to find descriptions of groups of individuals with unusual distributional characteristics  ...  Contrast Set Mining through Subgroup Discovery We present an approach to contrast set mining by means of subgroup discovery.  ... 
doi:10.1007/978-3-540-71701-0_61 dblp:conf/pakdd/KraljLGK07 fatcat:gepmeln7sbdhfipw2pebxfsfkm

Contrast Mining from Interesting Subgroups [chapter]

Laura Langohr, Vid Podpečan, Marko Petek, Igor Mozetič, Kristina Gruden
2012 Lecture Notes in Computer Science  
We propose to extend subgroup discovery by a second subgroup discovery step to find interesting subgroups of objects specific for a class in one or more contrast classes.  ...  First, a subgroup discovery method is applied. Then, contrast classes of objects are defined by using set theoretic functions on the discovered subgroups of objects.  ...  After reviewing subgroup discovery we introduced the construction of contrast classes on the discovered subgroups. Subgroup discovery then finds interesting subgroups in those contrast classes.  ... 
doi:10.1007/978-3-642-31830-6_28 fatcat:cvkk6lkryfggngduo6aswgsbai

Exploratory Data Mining for Subgroup Cohort Discoveries and Prioritization

Danlu Liu, William Baskett, David Beversdorf, Chi-Ren Shyu
2019 IEEE journal of biomedical and health informatics  
We have developed a novel subgroup discovery method which employs a deep exploratory mining process to slice and dice thousands of potential subpopulations and prioritize potential cohorts based on their  ...  explainable contrast patterns and which may provide interventionable insights.  ...  Michael Phinney for his implementation of the distributed version of contrast mining methods, and the University of Missouri Research Computing Support Services (RCSS) group for providing computing support  ... 
doi:10.1109/jbhi.2019.2939149 pmid:31494566 pmcid:PMC9341221 fatcat:n7evwo55u5ebjintvtojfr57yu

An overview on subgroup discovery: foundations and applications

Franciso Herrera, Cristóbal José Carmona, Pedro González, María José del Jesus
2010 Knowledge and Information Systems  
An overview related to the task of subgroup discovery is presented.  ...  Subgroup discovery is a data mining technique which extracts interesting rules with respect to a target variable.  ...  -An algorithm of subgroup discovery is used for discovering contrast sets in [77] . The idea is to solve the contrast set mining task by transforming it into a subgroup discovery task.  ... 
doi:10.1007/s10115-010-0356-2 fatcat:7o6opddi4bfbpnutkghq7i335u

SD-Map – A Fast Algorithm for Exhaustive Subgroup Discovery [chapter]

Martin Atzmueller, Frank Puppe
2006 Lecture Notes in Computer Science  
In this paper we present the novel SD-Map algorithm for exhaustive but efficient subgroup discovery.  ...  SD-Map guarantees to identify all interesting subgroup patterns contained in a data set, in contrast to heuristic or samplingbased methods.  ...  For subgroup discovery, the concept of interest, i.e., the target variable is fixed, in contrast to the arbitrary "rule head" of association rules.  ... 
doi:10.1007/11871637_6 fatcat:s3zlussx6bhyjj22izpyw5fgcu

Contrast Pattern Mining With the T1D Exchange Clinic Registry Reveals Complex Phenotypic Factors and Comorbidity Patterns Associated With Familial Versus Sporadic Type 1 Diabetes

Erin M. Tallon, Maria J. Redondo, Chi-Ren Shyu, Danlu Liu, Katrina Boles, Mark A. Clements
2022 Diabetes Care  
A contrast pattern mining algorithm detects significant differences in the frequencies of attributes across two patient subgroups.  ...  False discovery resulting from multiple-hypothesis testing was controlled using the BH procedure (false discovery rate, 0.1).  ... 
doi:10.2337/dc21-2239 pmid:35045157 pmcid:PMC8918263 fatcat:xrgqpnclk5di3j7u2wzeqgxosi

A Methodological View on Knowledge-Intensive Subgroup Discovery [chapter]

Martin Atzmueller, Frank Puppe
2006 Lecture Notes in Computer Science  
, and describe their application in the subgroup discovery setting.  ...  In this paper we present a methodological view on knowledge-intensive subgroup discovery: We introduce different classes and specific types of useful background knowledge, discuss their benefit and costs  ...  Conclusion In this paper we presented a methodological view on exploiting background knowledge for subgroup discovery.  ... 
doi:10.1007/11891451_28 fatcat:6ax6yqeigvhnncgc7ecvym4qyq

Distributed Subgroup Mining [chapter]

Michael Wurst, Martin Scholz
2006 Lecture Notes in Computer Science  
In this work we study two natural extensions of classical subgroup discovery to distributed settings.  ...  Subgroup discovery is a popular form of supervised rule learning, applicable to descriptive and predictive tasks.  ...  (2) ) in combination with the (usually unknown) utility of the best subgroup. In contrast, the global subgroup discovery algorithm evaluates less than 3.000 candidates.  ... 
doi:10.1007/11871637_40 fatcat:qdjjcavpizh4tjm4xwxkjmssoe

Observational Research, Randomised Trials, and Two Views of Medical Science

Jan P Vandenbroucke
2008 PLoS Medicine  
Thus, the post hoc discovery of subgroups in randomised trials has low prior probability, from which follows low credibility of subgroup findings.  ...  Subgroups and multiple analyses are a necessary part of observational research: otherwise, one cannot make new discoveries, nor quickly check discoveries by others.  ... 
doi:10.1371/journal.pmed.0050067 pmid:18336067 pmcid:PMC2265762 fatcat:ihumu3zecfd6zos2qpug5os7qa

Towards Polynomial Subgroup Discovery by Means of FCA

Aleksey Buzmakov
2020 European Conference on Artificial Intelligence  
The goal of subgroup discovery is to find groups of objects that are significantly different than "average" object w.r.t. some supervised information.  ...  SD-SOFIA fits subgroup discovery process in the framework of stable concept search. The proposed algorithm is evaluated on a dataset from UCI repository.  ...  By contrast, combing statistically significant subgroup discovery with heuristic methods is hard.  ... 
dblp:conf/ecai/Buzmakov20 fatcat:ugf4i3ljcbc67nlkujico3puxq

VIKAMINE – Open-Source Subgroup Discovery, Pattern Mining, and Analytics [chapter]

Martin Atzmueller, Florian Lemmerich
2012 Lecture Notes in Computer Science  
This paper presents an overview on the VIKAMINE 1 system for subgroup discovery, pattern mining and analytics.  ...  In contrast to general purpose data mining systems, it is specialized for the task of subgroup discovery and pattern mining.  ...  VIKAMINE Subgroup discovery and pattern mining are important descriptive data mining tasks.  ... 
doi:10.1007/978-3-642-33486-3_60 fatcat:bgs5qi6zmbeypimy7fgr47fufm

Heritable genotype contrast mining reveals novel gene associations specific to autism subgroups

Matt Spencer, Nicole Takahashi, Sounak Chakraborty, Judith Miles, Chi-Ren Shyu
2018 Journal of Biomedical Informatics  
High-contrast variant combinations are tested for significant subgroup associations. We apply this method by contrasting autism subgroups defined by severe or mild manifestations of a phenotype.  ...  Significant associations connected 286 genes to the subgroups, including 193 novel autism candidates. 71 pairs of genes have joint associations with subgroups, presenting opportunities to investigate interacting  ...  Zohreh Talebizadeh for the fruitful discussions on subgroup-focused research and potential follow-up directions for this study, and Dr.  ... 
doi:10.1016/j.jbi.2017.11.016 pmid:29197649 pmcid:PMC5788310 fatcat:vg27ti7cs5d3jpgwohj2wa44g4

AB023. S023. Identification and targeting of a poor-prognosis subgroup of pancreatic cancer

Veronique Veenstra, Frederike Dijk, Eline Soer, Lan Zhao, Johannes Halfwerk, Gerrit Hooijer, Naomi Donner, Helene Damhofer, Marco Marzano, Anne Steins, Cynthia Waasdorp, Olivier Busch (+14 others)
2018 Annals of Pancreatic Cancer  
Unsupervised class discovery in this singlecenter PDAC-only dataset identified four subgroups with distinct clinical manifestations.  ...  Experimental validation in models for PDAC subtyped using the modified classifier confirmed mesenchymal features and a highly invasive growth pattern for the poor-prognosis subtype in contrast to more  ...  Unsupervised class discovery in this singlecenter PDAC-only dataset identified four subgroups with distinct clinical manifestations.  ... 
doi:10.21037/apc.2018.ab023 fatcat:tjer5e345ff3fjsq5b6rza4rsi
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