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Volumn 29, Issue 3, 2011, Pages 495-525

An overview on subgroup discovery: Foundations and applications

Author keywords

Knowledge discovery; Subgroup discovery

Indexed keywords


EID: 79961211866     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-010-0356-2     Document Type: Review
Times cited : (256)

References (118)
  • 9
    • 29344452470 scopus 로고    scopus 로고
    • Semi-automatic visual subgroup mining using VIKAMINE
    • Atzmueller M, Puppe F (2005) Semi-automatic visual subgroup mining using VIKAMINE. J Univers Comput Sci 11(11): 1752-1765.
    • (2005) J Univers Comput Sci , vol.11 , Issue.11 , pp. 1752-1765
    • Atzmueller, M.1    Puppe, F.2
  • 11
    • 43449110077 scopus 로고    scopus 로고
    • A case-based approach for characterization and analysis of subgroup patterns
    • Atzmueller M, Puppe F (2008) A case-based approach for characterization and analysis of subgroup patterns. Appl Intell 28(3): 210-221.
    • (2008) Appl Intell , vol.28 , Issue.3 , pp. 210-221
    • Atzmueller, M.1    Puppe, F.2
  • 15
    • 65249124622 scopus 로고    scopus 로고
    • A semi-automatic approach for confounding-aware subgroup discovery
    • Atzmueller M, Puppe F, Buscher HP (2009) A semi-automatic approach for confounding-aware subgroup discovery. Int J Artif Intell Tools 18(1): 81-98.
    • (2009) Int J Artif Intell Tools , vol.18 , Issue.1 , pp. 81-98
    • Atzmueller, M.1    Puppe, F.2    Buscher, H.P.3
  • 16
    • 81155142872 scopus 로고    scopus 로고
    • Voltage sag source location from extracted rules using subgroup discovery
    • Barrera V, López B, Meléndez J, Sánchez J (2008) Voltage sag source location from extracted rules using subgroup discovery. Front Artif Intell Appl 184: 225-235.
    • (2008) Front Artif Intell Appl , vol.184 , pp. 225-235
    • Barrera, V.1    López, B.2    Meléndez, J.3    Sánchez, J.4
  • 17
    • 23044527560 scopus 로고    scopus 로고
    • Detecting group differences: mining contrast sets
    • Bay S, Pazzani M (2001) Detecting group differences: mining contrast sets. Data Mining Knowl Discov 5: 213-246.
    • (2001) Data Mining Knowl Discov , vol.5 , pp. 213-246
    • Bay, S.1    Pazzani, M.2
  • 23
    • 58549089000 scopus 로고    scopus 로고
    • One in a million: picking the right patterns
    • Bringmann B, Zimmermann A (2009) One in a million: picking the right patterns. Knowl Inf Syst 18(1): 61-81.
    • (2009) Knowl Inf Syst , vol.18 , Issue.1 , pp. 61-81
    • Bringmann, B.1    Zimmermann, A.2
  • 24
    • 53949099623 scopus 로고    scopus 로고
    • Subgroup discover in large size data sets preprocessed using stratified instance selection for increasing the presence of minority classes
    • Cano JR, García S, Herrera F (2008) Subgroup discover in large size data sets preprocessed using stratified instance selection for increasing the presence of minority classes. Patt Recognit Lett 29: 2156-2164.
    • (2008) Patt Recognit Lett , vol.29 , pp. 2156-2164
    • Cano, J.R.1    García, S.2    Herrera, F.3
  • 25
    • 48749106976 scopus 로고    scopus 로고
    • Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection
    • Cano JR, Herrera F, Lozano M, García S (2008) Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection. Expert Syst Appl 35: 1949-1965.
    • (2008) Expert Syst Appl , vol.35 , pp. 1949-1965
    • Cano, J.R.1    Herrera, F.2    Lozano, M.3    García, S.4
  • 28
    • 77957797485 scopus 로고    scopus 로고
    • NMEEF-SD: Non-dominated multi-objective evolutionary algorithm for extracting fuzzy rules in subgroup discovery
    • Carmona CJ, González P, del Jesus MJ, Herrera F (2010a) NMEEF-SD: Non-dominated multi-objective evolutionary algorithm for extracting fuzzy rules in subgroup discovery. IEEE Trans Fuzzy Syst 18(5): 958-970.
    • (2010) IEEE Trans Fuzzy Syst , vol.18 , Issue.5 , pp. 958-970
    • Carmona, C.J.1    González, P.2    Del Jesus, M.J.3    Herrera, F.4
  • 33
    • 34249966007 scopus 로고
    • The CN2 induction algorithm
    • Clark P, Niblett T (1989) The CN2 induction algorithm. Mach Learn 3: 261-283.
    • (1989) Mach Learn , vol.3 , pp. 261-283
    • Clark, P.1    Niblett, T.2
  • 35
    • 0036530772 scopus 로고    scopus 로고
    • A fast and elitist multiobjective genetic algorithm: NSGA-II
    • Deb K, Pratap A, Agrawal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2): 182-197.
    • (2002) IEEE Trans Evol Comput , vol.6 , Issue.2 , pp. 182-197
    • Deb, K.1    Pratap, A.2    Agrawal, S.3    Meyarivan, T.4
  • 37
    • 0036102015 scopus 로고    scopus 로고
    • Adaptive sampling methods for scaling up knowledge discovery algorithms
    • Domingo C, Gavaldá R, Watanabe O (2002) Adaptive sampling methods for scaling up knowledge discovery algorithms. Data Mining Knowl Discov 6(2): 131-152.
    • (2002) Data Mining Knowl Discov , vol.6 , Issue.2 , pp. 131-152
    • Domingo, C.1    Gavaldá, R.2    Watanabe, O.3
  • 39
    • 17744368529 scopus 로고    scopus 로고
    • On the representation, measurement, and discovery of fuzzy associations
    • Dubois D, Prade H, Sudkamp T (2005) On the representation, measurement, and discovery of fuzzy associations. IEEE Trans Fuzzy Syst 13: 250-262.
    • (2005) IEEE Trans Fuzzy Syst , vol.13 , pp. 250-262
    • Dubois, D.1    Prade, H.2    Sudkamp, T.3
  • 43
    • 0038433995 scopus 로고    scopus 로고
    • Expert-guided subgroup discovery: methodology and application
    • Gamberger D, Lavrac N (2002) Expert-guided subgroup discovery: methodology and application. J Artif Intell Res 17: 501-527.
    • (2002) J Artif Intell Res , vol.17 , pp. 501-527
    • Gamberger, D.1    Lavrac, N.2
  • 45
    • 0038500689 scopus 로고    scopus 로고
    • Active subgroup mining: a case study in coronary heart disease risk group detection
    • Gamberger D, Lavrac N (2003) Active subgroup mining: a case study in coronary heart disease risk group detection. Artif Intell Med 28(1): 27-57.
    • (2003) Artif Intell Med , vol.28 , Issue.1 , pp. 27-57
    • Gamberger, D.1    Lavrac, N.2
  • 50
    • 4744364732 scopus 로고    scopus 로고
    • Induction of comprehensible models for gene expression datasets by subgroup discovery methodology
    • Gamberger D, Lavrac N, Zelezny F, Tolar J (2004) Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. J Biomed Inform 37(4): 269-284.
    • (2004) J Biomed Inform , vol.37 , Issue.4 , pp. 269-284
    • Gamberger, D.1    Lavrac, N.2    Zelezny, F.3    Tolar, J.4
  • 52
    • 34948896034 scopus 로고    scopus 로고
    • Clinical data analysis based on iterative subgroup discovery: experiments in brain ischaemia data analysis
    • Gamberger D, Lavrac N, Krstaic A, Krstaic G (2007) Clinical data analysis based on iterative subgroup discovery: experiments in brain ischaemia data analysis. Appl Intell 27(3): 205-217.
    • (2007) Appl Intell , vol.27 , Issue.3 , pp. 205-217
    • Gamberger, D.1    Lavrac, N.2    Krstaic, A.3    Krstaic, G.4
  • 54
    • 68749120539 scopus 로고    scopus 로고
    • On subgroup discovery in numerical domains
    • Grosskreutz H, Rueping S (2009) On subgroup discovery in numerical domains. Data Mining Knowl Discov 19(2): 210-216.
    • (2009) Data Mining Knowl Discov , vol.19 , Issue.2 , pp. 210-216
    • Grosskreutz, H.1    Rueping, S.2
  • 57
    • 50149096917 scopus 로고    scopus 로고
    • Genetic fuzzy systems: taxomony, current research trends and prospects
    • Herrera F (2008) Genetic fuzzy systems: taxomony, current research trends and prospects. Evol Intell 1: 27-46.
    • (2008) Evol Intell , vol.1 , pp. 27-46
    • Herrera, F.1
  • 61
    • 34548285425 scopus 로고    scopus 로고
    • Evolutionary fuzzy rule induction process for subgroup discovery: a case study in marketing
    • del Jesus MJ, González P, Herrera F, Mesonero M (2007) Evolutionary fuzzy rule induction process for subgroup discovery: a case study in marketing. IEEE Trans Fuzzy Syst 15(4): 578-592.
    • (2007) IEEE Trans Fuzzy Syst , vol.15 , Issue.4 , pp. 578-592
    • Del Jesus, M.J.1    González, P.2    Herrera, F.3    Mesonero, M.4
  • 65
    • 34548257712 scopus 로고    scopus 로고
    • Using subgroup discovery to analyze the UK traffic data
    • Kavsek B, Lavrac N (2004) Using subgroup discovery to analyze the UK traffic data. Metodoloski Zvezki 1(1): 249-264.
    • (2004) Metodoloski Zvezki , vol.1 , Issue.1 , pp. 249-264
    • Kavsek, B.1    Lavrac, N.2
  • 66
    • 33747881454 scopus 로고    scopus 로고
    • APRIORI-SD: adapting association rule learning to subgroup discovery
    • Kavsek B, Lavrac N (2006) APRIORI-SD: adapting association rule learning to subgroup discovery. Appl Artif Intell 20: 543-583.
    • (2006) Appl Artif Intell , vol.20 , pp. 543-583
    • Kavsek, B.1    Lavrac, N.2
  • 75
    • 61749095466 scopus 로고    scopus 로고
    • Mining census data for spatial effects on mortality
    • Kloesgen W, May M, Petch J (2003) Mining census data for spatial effects on mortality. Intell Data Anal 7: 521-540.
    • (2003) Intell Data Anal , vol.7 , pp. 521-540
    • Kloesgen, W.1    May, M.2    Petch, J.3
  • 77
    • 60049090613 scopus 로고    scopus 로고
    • CSM-SD: methodology for contrast set mining through subgroup discovery
    • Kralj-Novak P, Lavrac N, Gamberger D, Krstacic A (2009) CSM-SD: methodology for contrast set mining through subgroup discovery. J Biomed Inform 42(1): 113-122.
    • (2009) J Biomed Inform , vol.42 , Issue.1 , pp. 113-122
    • Kralj-Novak, P.1    Lavrac, N.2    Gamberger, D.3    Krstacic, A.4
  • 78
    • 61749084093 scopus 로고    scopus 로고
    • Supervised descriptive rule discovery: a unifying survey of constrast set, emerging pateern and subgroup mining
    • Kralj-Novak P, Lavrac N, Webb GI (2009) Supervised descriptive rule discovery: a unifying survey of constrast set, emerging pateern and subgroup mining. J Mach Learn Res 10: 377-403.
    • (2009) J Mach Learn Res , vol.10 , pp. 377-403
    • Kralj-Novak, P.1    Lavrac, N.2    Webb, G.I.3
  • 79
    • 40749150053 scopus 로고    scopus 로고
    • Temporal analysis of political instability through descriptive subgroup discovery
    • Lambach D, Gamberger D (2008) Temporal analysis of political instability through descriptive subgroup discovery. Confl Manag Peace Sci 25: 19-32.
    • (2008) Confl Manag Peace Sci , vol.25 , pp. 19-32
    • Lambach, D.1    Gamberger, D.2
  • 84
    • 3242791702 scopus 로고    scopus 로고
    • Decision support through subgroup discovery: three case studies and the lessons learned
    • Lavrac N, Cestnik B, Gamberger D, Flach PA (2004) Decision support through subgroup discovery: three case studies and the lessons learned. Mach Learn 57(1-2): 115-143.
    • (2004) Mach Learn , vol.57 , Issue.1-2 , pp. 115-143
    • Lavrac, N.1    Cestnik, B.2    Gamberger, D.3    Flach, P.A.4
  • 86
    • 26944438300 scopus 로고    scopus 로고
    • Local patterns: theory and practice of constraint-based relational subgroup discovery
    • Springer, LNCS
    • Lavrac N, Zelezny F, Dzeroski S (2005) Local patterns: theory and practice of constraint-based relational subgroup discovery. In: International seminar on local pattern detection, vol 3539. Springer, LNCS, pp 71-88.
    • (2005) In: International seminar on local pattern detection , vol.3539 , pp. 71-88
    • Lavrac, N.1    Zelezny, F.2    Dzeroski, S.3
  • 93
    • 84901456921 scopus 로고    scopus 로고
    • Discovering interesting prediction rules wih a genetic algorithm
    • Noda E, Freitas AA, Lopes HS (1999) Discovering interesting prediction rules wih a genetic algorithm. IEEE Congr Evol Comput 2: 1322-1329.
    • (1999) IEEE Congr Evol Comput , vol.2 , pp. 1322-1329
    • Noda, E.1    Freitas, A.A.2    Lopes, H.S.3
  • 95
    • 33845663518 scopus 로고    scopus 로고
    • Educational data mining: a survey from 1995 to 2005
    • Romero C, Ventura S (2007) Educational data mining: a survey from 1995 to 2005. Expert Syst Appl 33(1): 135-146.
    • (2007) Expert Syst Appl , vol.33 , Issue.1 , pp. 135-146
    • Romero, C.1    Ventura, S.2
  • 96
    • 56349162269 scopus 로고    scopus 로고
    • Evolutionary algorithm for subgroup discovery in e-learning: a practical application using Moodle data
    • Romero C, González P, Ventura S, del Jesus MJ, Herrera F (2009) Evolutionary algorithm for subgroup discovery in e-learning: a practical application using Moodle data. Expert Syst Appl 36: 1632-1644.
    • (2009) Expert Syst Appl , vol.36 , pp. 1632-1644
    • Romero, C.1    González, P.2    Ventura, S.3    Del Jesus, M.J.4    Herrera, F.5
  • 98
    • 0141719772 scopus 로고    scopus 로고
    • Finding the most interesting patterns in a database quickly by using sequential sampling
    • Scheffer T, Wrobel S (2002) Finding the most interesting patterns in a database quickly by using sequential sampling. J Mach Learn Res 3: 833-862.
    • (2002) J Mach Learn Res , vol.3 , pp. 833-862
    • Scheffer, T.1    Wrobel, S.2
  • 99
  • 100
    • 26944437744 scopus 로고    scopus 로고
    • Knowledge-based sampling for subgroup discovery
    • Springer, LNAI
    • Scholz M (2005) Knowledge-based sampling for subgroup discovery. In: International seminar on local pattern detection, vol 3539. Springer, LNAI, pp 171-189.
    • (2005) In: International seminar on local pattern detection , vol.3539 , pp. 171-189
    • Scholz, M.1
  • 106
    • 85008042564 scopus 로고    scopus 로고
    • Learning relational descriptions of differentially expressed gene groups
    • Trajkovski I, Zelezny F, Lavrac N, Tolar J (2008) Learning relational descriptions of differentially expressed gene groups. IEEE Trans Syst Man Cybern C 38(1): 16-25.
    • (2008) IEEE Trans Syst Man Cybern C , vol.38 , Issue.1 , pp. 16-25
    • Trajkovski, I.1    Zelezny, F.2    Lavrac, N.3    Tolar, J.4
  • 111
    • 0016458950 scopus 로고
    • The concept of a linguistic variable and its applications to approximate reasoning
    • Parts I, II, III
    • Zadeh LA (1975) The concept of a linguistic variable and its applications to approximate reasoning. Parts I, II, III. Inf Sci 8-9: 199-249, 301-357, 43-80.
    • (1975) Inf Sci , vol.8-9
    • Zadeh, L.A.1
  • 112
    • 32144454875 scopus 로고    scopus 로고
    • Propositionalization-based relational subgroup discovery with RSD
    • Zelezny F, Lavrac N (2006) Propositionalization-based relational subgroup discovery with RSD. Machine Learning 62: 33-63.
    • (2006) Machine Learning , vol.62 , pp. 33-63
    • Zelezny, F.1    Lavrac, N.2
  • 117
    • 69549138078 scopus 로고    scopus 로고
    • Cluster-grouping: from subgroup discovery to clustering
    • Zimmerman A, de Raedt L (2009) Cluster-grouping: from subgroup discovery to clustering. Mach Learn 77(1): 125-159.
    • (2009) Mach Learn , vol.77 , Issue.1 , pp. 125-159
    • Zimmerman, A.1    de Raedt, L.2


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