Cluster analysis
R. Nugent and W. Stuetzle
Clustering with confidence: A low-dimensional binning approach.
In Classification as a tool for research, H. Jocarek-Junge and Claus
Weihs (Eds), Springer, 2010, pp. 117-125.
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A. Youn, D.J. Reiss, and W. Stuetzle
Learning transcriptional networks from the integration of ChIP-chip and
expression data in a nonparametric model.
Bioinformatics 2010; doi: 10.1093/bioinformatics/btq289
W. Stuetzle and R. Nugent
A generalized single linkage method for estimating the cluster tree of a
density.
Journal of Computational and Graphical Statistics, Vol 19, No. 2, 2010, pp.
397--418.
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Online supplement
A. Murua, W. Stuetzle, J. Tantrum, and S. Sieberts
Model based document classification and clustering.
International Journal of Tomography & Statistics, Vol. 8, No. W08, 2008, pp.
1--24.
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A. Murua, L. Stanberry, and W. Stuetzle
On Potts model clustering, kernel k-means, and density estimation.
Journal of Computational and Graphical Statistics, Vol. 17, No. 4, 2008, pp.
629--658.
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W. Stuetzle
Estimating the cluster tree of a density
by analyzing the
minimal spanning tree of a sample.
Journal of Classification, Vol. 20, No. 5, 2003, pp. 25-47.
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J. Tantrum, A. Murua, and W. Stuetzle
Hierarchical model-based clustering of large datasets through
Fractionation and Refractionation.
Joint work with Proceedings of the 8th
International Conference on Knowledge Discovery and Data Mining (KDD02), 2002,
pp. 183--190.
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J. Tantrum, A. Murua, and W. Stuetzle
Assessment and pruning of hierarchical model-based clustering.
Proceedings of the 9th
International Conference on Knowledge Discovery and Data Mining (KDD03), 2003,
pp. 197 -- 205.
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Principal curves and nonlinear principal components
T. DeRose, T. Duchamp, H. Hoppe, J.A. McDonald, and W. Stuetzle
Reconstructing two-dimensional manifolds from scattered data: motivation and
background.
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T. Duchamp and W. Stuetzle
Extremal properties of principal curves in the plane.
Annals of Statistics, Vol. 24, No. 4, 1996, pp. 1511 - 1520.
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T. Duchamp and W. Stuetzle
Geometric properties of principal curves in the plane.
In Robust Statistics, Data Analysis, ad Computer
Intensive Methods, Helmut Rieder, ed, Springer Lecture Notes in Statistics No. 109,
1995.
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A. Buja, D. Donnell, and W. Stuetzle
Analysis of additive dependencies and concurvities using smallest additive
principal components
Discussion paper, Annals of Statistics, Vol. 22, 1994, pp. 1635--1673.
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T. Hastie and W. Stuetzle
Principal curves.
Journal of the
American Statistical Association, Vol. 84, 1989, pp. 502-516.
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Unsupervised learning: Estimating the cluster tree of a density from the minimal spanning tree of a sample. Powerpoint presentation
Unsupervised learning: Statistical and computational perspectives. Powerpoint presentation
What are the effects of "Bagging"? Some experimental and theoretical results. Powerpoint presentation
Generalized single linkage clustering. Powerpoint presentation