메뉴 건너뛰기




Volumn 23, Issue 1, 2011, Pages 128-168

Learning model trees from evolving data streams

Author keywords

Concept drift; Incremental algorithms; Model trees; Non stationary data streams; On line change detection; On line learning; Regression trees; Stream data mining

Indexed keywords

CONCEPT DRIFTS; INCREMENTAL ALGORITHM; MODEL TREES; NONSTATIONARY DATA; ONLINE CHANGE DETECTION; ONLINE LEARNING; REGRESSION TREES; STREAM DATA MINING;

EID: 79960103750     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-010-0201-y     Document Type: Article
Times cited : (265)

References (51)
  • 4
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • Breiman L (1998) Arcing classifiers. Ann Stat 26(3):801-824
    • (1998) Ann Stat , vol.26 , Issue.3 , pp. 801-824
    • Breiman, L.1
  • 6
    • 0000951197 scopus 로고
    • Piecewise polynomial regression trees
    • Chaudhuri P, Huang M, Loh W, Yao R (1994) Piecewise polynomial regression trees. Stat Sin 4:143-167
    • (1994) Stat Sin , vol.4 , pp. 143-167
    • Chaudhuri, P.1    Huang, M.2    Loh, W.3    Yao, R.4
  • 8
    • 79960099787 scopus 로고    scopus 로고
    • CUBIST Accessed 19 Jan 2010
    • CUBIST (2009) RuleQuest research. http://www.rulequest.com/cubist-info. html. Accessed 19 Jan 2010
    • (2009) RuleQuest Research
  • 9
    • 70349852947 scopus 로고    scopus 로고
    • Change (detection) you can believe in: Finding distributional shifts in data streams
    • Springer Berlin
    • Dasu T, Krishnan S, Lin D, Venkatasubramanian S, Yi K (2009) Change (detection) you can believe in: finding distributional shifts in data streams. In: Proc IDA'09. Springer, Berlin, pp 21-34
    • (2009) Proc IDA'09 , pp. 21-34
    • Dasu, T.1    Krishnan, S.2    Lin, D.3    Venkatasubramanian, S.4    Yi, K.5
  • 11
    • 0000582742 scopus 로고
    • Statistical theory: The prequential approach
    • Dawid AP (1984) Statistical theory: the prequential approach. J R Stat Soc A 147:278-292
    • (1984) J R Stat Soc A , vol.147 , pp. 278-292
    • Dawid, A.P.1
  • 14
    • 0002432565 scopus 로고
    • Multivariate adaptive regression splines
    • doi:10.1214/aos/1176347963
    • Friedman JH (1991) Multivariate adaptive regression splines. J Ann Stat 19(1):1-67. doi:10.1214/aos/ 1176347963
    • (1991) J Ann Stat , vol.19 , Issue.1 , pp. 1-67
    • Friedman, J.H.1
  • 19
    • 0037174204 scopus 로고    scopus 로고
    • Prediction algorithms and confidence measures based on algorithmic randomness theory
    • DOI 10.1016/S0304-3975(02)00100-7, PII S0304397502001007, Natural Computing
    • Gammerman A, Vovk V (2002) Prediction algorithms and confidence measures based on algorithmic randomness theory. J Theor Comput Sci 287:209-217 (Pubitemid 35019166)
    • (2002) Theoretical Computer Science , vol.287 , Issue.1 , pp. 209-217
    • Gammerman, A.1    Vovk, V.2
  • 20
    • 33947281129 scopus 로고    scopus 로고
    • Hedging predictions in machine learning
    • DOI 10.1093/comjnl/bxl065
    • Gammerman A, Vovk V (2007) Hedging predictions in machine learning. Comput J 50:151-163 (Pubitemid 46416421)
    • (2007) Computer Journal , vol.50 , Issue.2 , pp. 151-163
    • Gammerman, A.1    Vovk, V.2
  • 21
    • 70449102582 scopus 로고    scopus 로고
    • A general framework for mining concept-drifting data streams with skewed distributions
    • Philadelphia, PA
    • Gao J, Fan W, Han J, Yu PS (2007) A general framework for mining concept-drifting data streams with skewed distributions. In: Proc 7th int conf on data mining, SIAM, Philadelphia, PA
    • (2007) Proc 7th Int Conf on Data Mining SIAM
    • Gao, J.1    Fan, W.2    Han, J.3    Yu, P.S.4
  • 24
    • 84947403595 scopus 로고
    • Probability for sums of bounded random variables
    • Hoeffding W (1963) Probability for sums of bounded random variables. J Am Stat Assoc 58:13-30
    • (1963) J Am Stat Assoc , vol.58 , pp. 13-30
    • Hoeffding, W.1
  • 29
    • 0002714595 scopus 로고
    • Employing linear regression in regression tree leaves
    • Wiley New York
    • Karalic A (1992) Employing linear regression in regression tree leaves. In: Proc 10th European conf on artificial intelligence. Wiley, New York, pp 440-441
    • (1992) Proc 10th European Conf on Artificial Intelligence , pp. 440-441
    • Karalic, A.1
  • 33
    • 0036556537 scopus 로고    scopus 로고
    • Regression trees with unbiased variable selection and interaction detection
    • Loh W (2002) Regression trees with unbiased variable selection and interaction detection (2002). Stat Sin 12:361-386 (Pubitemid 36116175)
    • (2002) Statistica Sinica , vol.12 , Issue.2 , pp. 361-386
    • Loh, W.-Y.1
  • 35
    • 16244377118 scopus 로고    scopus 로고
    • Test of Page-Hinckley, an approach for fault detection in an agro-alimentary production system
    • 2004 5th Asian Control Conference
    • Mouss H, Mouss D, Mouss N, Sefouhi L (2004) Test of Page-Hinckley, an approach for fault detection in an agro-alimentary production system. In: Proc 5th Asian control conference, vol 2. IEEE Computer Society, Los Alamitos, CA, pp 815-818 (Pubitemid 40455896)
    • (2004) 2004 5th Asian Control Conference , vol.2 , pp. 815-818
    • Mouss, H.1    Mouss, D.2    Mouss, N.3    Sefouhi, L.4
  • 36
    • 33747646201 scopus 로고
    • Decision theoretic sub-sampling for induction on large databases
    • Morgan Kaufmann San Francisco
    • Musick R, Catlett J, Russell S (1993) Decision theoretic sub-sampling for induction on large databases. In: Proc 10th int conf on machine learning. Morgan Kaufmann, San Francisco, pp 212-219
    • (1993) Proc 10th Int Conf on Machine Learning , pp. 212-219
    • Musick, R.1    Catlett, J.2    Russell, S.3
  • 37
    • 22944451818 scopus 로고    scopus 로고
    • Improving the centered CUSUMS statistic for structural break detection in time series
    • Springer, Berlin
    • Pang KP, Ting KM (2005) Improving the centered CUSUMS statistic for structural break detection in time series. In: Proc 17th Australian joint conf on artificial intelligence, LNCS, vol 3339. Springer, Berlin, pp 402-413
    • (2005) Proc 17th Australian Joint Conf on Artificial Intelligence, LNCS , vol.3339 , pp. 402-413
    • Pang, K.P.1    Ting, K.M.2
  • 39
    • 30044434365 scopus 로고    scopus 로고
    • Incremental learning of linear model trees
    • DOI 10.1007/s10994-005-1121-8
    • Potts D, Sammut C (2005) Incremental learning of linear model trees. J Mach Learn 61:5-48. doi:10.1007/ s10994-005-1121-8 (Pubitemid 43049361)
    • (2005) Machine Learning , vol.61 , Issue.1-3 , pp. 5-48
    • Potts, D.1    Sammut, C.2
  • 41
    • 84942845956 scopus 로고    scopus 로고
    • A topic detection, tracking, and trend analysis using self-organizing neural networks
    • Advances in Knowledge Discovery and Data Mining 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001 Proceedings
    • Rajaraman K, Tan (2001) A topic detection, tracking, and trend analysis using self-organizing neural networks. In: Proc 5th Pacific-Asian conf on knowledge discovery and data mining, LNCS, vol 2035. Springer, Berlin, pp 102-107 (Pubitemid 33255099)
    • (2001) Lecture Notes in Computer Science , Issue.2035 , pp. 102-107
    • Rajaraman, K.1    Tan, A.-H.2
  • 42
    • 62449145679 scopus 로고    scopus 로고
    • Online reliability estimates for individual predictions in data streams
    • IEEE Computer Society, Los Alamitos, CA
    • Rodrigues PP, Gama J, Bosnic Z (2008) Online reliability estimates for individual predictions in data streams. In: Proc IEEE int conf on data mining workshops. IEEE Computer Society, Los Alamitos, CA, pp 36-45
    • (2008) Proc IEEE Int Conf on Data Mining Workshops , pp. 36-45
    • Rodrigues, P.P.1    Gama, J.2    Bosnic, Z.3
  • 43
    • 77951175741 scopus 로고    scopus 로고
    • Detection in climate data over the Iberian peninsula
    • IEEE Computer Society, Los Alamitos, CA
    • Sebastiao R, Rodrigues PP, Gama J (2009) Change detection in climate data over the Iberian peninsula. In: Proc IEEE int conf on data mining workshops. IEEE Computer Society, Los Alamitos, CA, pp 248-253
    • (2009) Proc IEEE Int Conf on Data Mining Workshops , pp. 248-253
    • Sebastiao, R.1    Rodrigues, P.P.2    Gama, J.3
  • 44
    • 14344261867 scopus 로고
    • Modeling for recursive partitioning and variable selection
    • Heidelberg, Physica Verlag
    • Siciliano R, Mola F (1994) Modeling for recursive partitioning and variable selection. In: Proc int conf on computational statistics. Physica Verlag, Heidelberg, pp 172-177
    • (1994) Proc Int Conf on Computational Statistics , pp. 172-177
    • Siciliano, R.1    Mola, F.2
  • 47
    • 0001831521 scopus 로고    scopus 로고
    • Functional models for regression tree leaves
    • Morgan Kaufmann San Francisco
    • Torgo L (1997) Functional models for regression tree leaves. In: Proc 14th int conf on machine learning. Morgan Kaufmann, San Francisco, pp 385-393
    • (1997) Proc 14th Int Conf on Machine Learning , pp. 385-393
    • Torgo, L.1
  • 50
    • 31644441593 scopus 로고    scopus 로고
    • WEKA 3, Accessed 19 Jan 2010
    • WEKA 3 (2005) Data Mining Software in Java. http://www.cs.waikato.ac.nz/ ml/weka. Accessed 19 Jan 2010
    • (2005) Data Mining Software in Java
  • 51
    • 0030126609 scopus 로고    scopus 로고
    • Learning in the presence of concept drift and hidden contexts
    • Widmer G, Kubat M (1996) Learning in the presence of concept drifts and hidden contexts. J Mach Learn 23:69-101. doi:10.1007/BF00116900 (Pubitemid 126737384)
    • (1996) Machine Learning , vol.23 , Issue.1 , pp. 69-101
    • Widmer, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.