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Volumn , Issue , 2007, Pages 197-208

Modelling and analysing interval data

Author keywords

[No Author keywords available]

Indexed keywords

DATA HANDLING; DISCRIMINANT ANALYSIS;

EID: 77956510166     PISSN: 14318814     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-70981-7_23     Document Type: Conference Paper
Times cited : (21)

References (15)
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    • (2000) Analysis of Symbolic Data , pp. 106-124
    • Bertrand, P.1    Goupil, F.2
  • 2
    • 0041743064 scopus 로고    scopus 로고
    • From the statistics of data to the statistics of knowledge: Symbolic data analysis
    • BILLARD, L. and DIDAY, E. (2003): From the Statistics of Data to the Statistics of Knowledge: Symbolic Data Analysis. Journal of the American Statistical Association, 98, 462, 470-487.
    • (2003) Journal of the American Statistical Association , vol.98 , Issue.462 , pp. 470-487
    • Billard, L.1    Diday, E.2
  • 5
    • 0012393548 scopus 로고    scopus 로고
    • Dynamical clustering algorithm of interval data: Optimization of an adequacy criterion based on hausdorff distance
    • A. Sokolowski and H.-H. Bock (Eds.): Springer, Heidelberg
    • CHAVENT, M. and LECHEVALLIER, Y. (2002): Dynamical Clustering Algorithm of Interval Data: Optimization of an Adequacy Criterion Based on Hausdorff Distance. In: A. Sokolowski and H.-H. Bock (Eds.): Classification, Clustering and Data Analysis. Springer, Heidelberg, 53-59.
    • (2002) Classification, Clustering and Data Analysis , pp. 53-59
    • Chavent, M.1    Lechevallier, Y.2
  • 6
    • 33750157606 scopus 로고    scopus 로고
    • Symbolic principal component analysis
    • H.-H. Bock and E. Diday (Eds.): Springer, Heidelberg
    • CHOUAKRIA, A., CAZES, P. and DIDAY, E. (2000): Symbolic Principal Component Analysis. In: H.-H. Bock and E. Diday (Eds.): Analysis of Symbolic Data. Springer, Heidelberg, 200-212.
    • (2000) Analysis of Symbolic Data , pp. 200-212
    • Chouakria, A.1    Cazes, P.2    Diday, E.3
  • 7
    • 33750164227 scopus 로고    scopus 로고
    • Dynamic clustering for interval data based on L2 distance
    • DE CARVALHO, F.A.T., BRITO, P. and BOCK, H.-H. (2006): Dynamic Clustering for Interval Data Based on L2 Distance. Computational Statistics, 21, 2, 231 250.
    • (2006) Computational Statistics , vol.21 , Issue.2 , pp. 231-250
    • De Carvalho, F.A.T.1    Brito, P.2    Bock, H.-H.3
  • 9
    • 0019111672 scopus 로고
    • Clustering analysis
    • K.S. Fu (Ed.): Springer, Heidelberg
    • DIDAY, E. and SIMON, J.J. (1976): Clustering Analysis. In: K.S. Fu (Ed.): Digital Pattern Recognition. Springer, Heidelberg, 47-94.
    • (1976) Digital Pattern Recognition , pp. 47-94
    • Diday, E.1    Simon, J.J.2
  • 10
    • 33750190295 scopus 로고    scopus 로고
    • Linear discriminant analysis for interval data
    • DUARTE SILVA, A.P. and BRITO, P. (2006): Linear Discriminant Analysis for Interval Data. Computational Statistics, 21, 2, 289-308.
    • (2006) Computational Statistics , vol.21 , Issue.2 , pp. 289-308
    • Duarte Silva, A.P.1    Brito, P.2
  • 11
    • 84988620563 scopus 로고    scopus 로고
    • Principal component analysis for non-precise data
    • M. Vichi et al (Eds.): . Springer
    • LAURO, C. and PALUMBO, F. (2005): Principal Component Analysis for Non-Precise Data. In: M. Vichi et al (Eds.): New Developments in Classification and Data Analysis. Springer, 173-184.
    • (2005) New Developments in Classification and Data Analysis , pp. 173-184
    • Lauro, C.1    Palumbo, F.2
  • 13
    • 22944445790 scopus 로고    scopus 로고
    • Univariate and multivariate linear regression methods to predict interval-valued features
    • Lecture Notes on Artificial Intelligence, Springer
    • NETO, E.A.L., DE CARVALHO, F.A.T. and TENORIO, C. (2004): Univariate and Multivariate Linear Regression Methods to Predict Interval-Valued Features. In: AI2004:Advances in Artificial Intelligence. Lecture Notes on Artificial Intelligence, Springer, 526-537.
    • (2004) AI2004:Advances in Artificial Intelligence , pp. 526-537
    • Neto, E.A.L.1    De Carvalho, F.A.T.2    Tenorio, C.3
  • 14
    • 0346724786 scopus 로고    scopus 로고
    • Clustering of interval data based on city-block distances
    • SOUZA, R.M.C.R. and DE CARVALHO, F.A.T. (2004): Clustering of Interval Data Based on City-Block Distances. Pattern Recognition Letters, 25, 3, 353-365.
    • (2004) Pattern Recognition Letters , vol.25 , Issue.3 , pp. 353-365
    • Souza, R.M.C.R.1    De Carvalho, F.A.T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.