메뉴 건너뛰기




Volumn , Issue , 2011, Pages 753-760

Tree preserving embedding

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER SEPARATION; COMPLEX DATA; EXPLORATORY DATA ANALYSIS; FINITE SAMPLES; HIGH DIMENSIONAL DATA; LOW-DIMENSIONAL SPACES; TOPOLOGICAL NOTIONS; VISUALIZATION METHOD; VISUALIZATION TECHNIQUE;

EID: 80053446255     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (34)
  • 3
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • DOI 10.1162/089976603321780317
    • Belkin, M and Niyogi, P. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput, 15:1373-1396, 2003. (Pubitemid 37049796)
    • (2003) Neural Computation , vol.15 , Issue.6 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 5
    • 77951952667 scopus 로고    scopus 로고
    • Characterization, stability and convergence of hierarchical clustering methods
    • Carlsson, G and Mémoli, F. Characterization, stability and convergence of hierarchical clustering methods. J Mach Learn Res, 11:1425-1470, 2010.
    • (2010) J Mach Learn Res , vol.11 , pp. 1425-1470
    • Carlsson, G.1    Mémoli, F.2
  • 7
    • 70350344696 scopus 로고    scopus 로고
    • Local multidimensional scaling for nonlinear dimension reduction, graph drawing, and proximity analysis
    • Chen, L and Buja, A. Local multidimensional scaling for nonlinear dimension reduction, graph drawing, and proximity analysis. J Am Stat Assoc, 104:209-219, 2009.
    • (2009) J Am Stat Assoc , vol.104 , pp. 209-219
    • Chen, L.1    Buja, A.2
  • 11
    • 0001859411 scopus 로고    scopus 로고
    • The Realization Problem for Euclidean Minimum Spanning Trees is NP-Hard
    • Eades, P. The realization problem for euclidean minimum spanning trees is np-hard. Algorithmica, 16:60-82, 1996. (Pubitemid 126418816)
    • (1996) Algorithmica (New York) , vol.16 , Issue.1 , pp. 60-82
    • Eades, P.1    Whitesides, S.2
  • 13
    • 0001120850 scopus 로고
    • Minimum spanning trees and single linkage cluster analysis
    • Gower, J C and Ross, G J S. Minimum spanning trees and single linkage cluster analysis. Appl Stat, 18:54-64, 1969.
    • (1969) Appl Stat , vol.18 , pp. 54-64
    • Gower, J.C.1    Ross, G.J.S.2
  • 15
    • 33748888529 scopus 로고
    • Statistical theory in clustering
    • Hartigan, J A. Statistical theory in clustering. J Classif, pp. 63-76, 1985.
    • (1985) J Classif , pp. 63-76
    • Hartigan, J.A.1
  • 17
    • 0028428774 scopus 로고
    • A database for handwritten text recognition research
    • Hull, J J. A database for handwritten text recognition research. IEEE T Pattern Anal, 16:550-554, 1994.
    • (1994) IEEE T Pattern Anal , vol.16 , pp. 550-554
    • Hull, J.J.1
  • 18
    • 0014129195 scopus 로고
    • Hierarchical clustering schemes
    • Johnson, S C. Hierarchical clustering schemes. Psychometrika, 32:241-254, 1967.
    • (1967) Psychometrika , vol.32 , pp. 241-254
    • Johnson, S.C.1
  • 21
    • 15744396339 scopus 로고    scopus 로고
    • Taxonomic utility of a phylogenetic analysis of phosphoglycerate kinase proteins of archaea, bacteria, and eukaryota: Insights by bayesian analyses
    • Pollack, J D, Li, Q, and K, Pearl D. Taxonomic utility of a phylogenetic analysis of phosphoglycerate kinase proteins of archaea, bacteria, and eukaryota: Insights by bayesian analyses. Mol Phylogenet Evol, 35:420-430, 2005.
    • (2005) Mol Phylogenet Evol , vol.35 , pp. 420-430
    • Pollack, J.D.1    Li, Q.2    Pearl, D.K.3
  • 22
    • 84925711202 scopus 로고    scopus 로고
    • Distributional scaling: An algorithm for structure-preserving embedding of metric and non-metric spaces
    • Quist, M and Yona, G. Distributional scaling: an algorithm for structure-preserving embedding of metric and non-metric spaces. J Mach Learn Res, 5:399-420, 2004.
    • (2004) J Mach Learn Res , vol.5 , pp. 399-420
    • Quist, M.1    Yona, G.2
  • 23
    • 0347380866 scopus 로고    scopus 로고
    • Optimal cluster preserving embedding of nonmetric proximity data
    • Roth, V, Laub, J, Kawanabe, M, and Buhmann, J M. Optimal cluster preserving embedding of nonmetric proximity data. IEEE T Pattern Anal, 25:1540-1551, 2003.
    • (2003) IEEE T Pattern Anal , vol.25 , pp. 1540-1551
    • Roth, V.1    Laub, J.2    Kawanabe, M.3    Buhmann, J.M.4
  • 24
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • DOI 10.1126/science.290.5500.2323
    • Roweis, S T and Saul, L K. Nonlinear dimensionality reduction by locally linear embedding. Science, 290:2323-2326, 2000. (Pubitemid 32041578)
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 25
    • 2342517502 scopus 로고    scopus 로고
    • Think globally, fit locally: Unsupervised learning of low dimensional manifolds
    • Saul, L K and Roweis, S T. Think globally, fit locally: Unsupervised learning of low dimensional manifolds. J Mach Learn Res, 4:119-155, 2003.
    • (2003) J Mach Learn Res , vol.4 , pp. 119-155
    • Saul, L.K.1    Roweis, S.T.2
  • 27
    • 0042021603 scopus 로고
    • Multidimensional scaling, tree-fitting, and clustering
    • Shepard, R N. Multidimensional scaling, tree-fitting, and clustering. Science, 210:390-398, 1980.
    • (1980) Science , vol.210 , pp. 390-398
    • Shepard, R.N.1
  • 28
    • 0024704073 scopus 로고
    • Classification of radar returns from the ionosphere using neural networks
    • Sigillito, V G, Wing, S P, Hutton, L V, and Baker, K B. Classification of radar returns from the ionosphere using neural networks. J Hopkins Apl Tech D, 10:262-266, 1989.
    • (1989) J Hopkins Apl Tech D , vol.10 , pp. 262-266
    • Sigillito, V.G.1    Wing, S.P.2    Hutton, L.V.3    Baker, K.B.4
  • 29
    • 0037560966 scopus 로고    scopus 로고
    • Estimating the cluster tree of a density by analyzing the minimal spanning tree of a sample
    • DOI 10.1007/s00357-003-0004-6
    • Stuetzle, W. Estimating the cluster tree of a density by analyzing the minimal spanning tree of a sample. J Classif, 20:25-47, 2003. (Pubitemid 36742925)
    • (2003) Journal of Classification , vol.20 , Issue.1 , pp. 25-47
    • Stuetzle, W.1
  • 30
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • DOI 10.1126/science.290.5500.2319
    • Tenenbaum, J B, De Silva, V, and Langford, J C. A global geometric framework for nonlinear dimensionality reduction. Science, 290:2319-2323, 2000. (Pubitemid 32041577)
    • (2000) Science , vol.290 , Issue.5500 , pp. 2319-2323
    • Tenenbaum, J.B.1    De Silva, V.2    Langford, J.C.3
  • 32
    • 77949507946 scopus 로고    scopus 로고
    • Information retrieval perspective to nonlinear dimensionality reduction for data visualization
    • Venna, J, Peltonen, J, Nybo, K, Aidos, H, and Samuel, K. Information retrieval perspective to nonlinear dimensionality reduction for data visualization. J Mach Learn Res, 11:451-490, 2010.
    • (2010) J Mach Learn Res , vol.11 , pp. 451-490
    • Venna, J.1    Peltonen, J.2    Nybo, K.3    Aidos, H.4    Samuel, K.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.