A General Framework for a Principled Hierarchical Visualization of Multivariate Data
作者： Ata Kabán , Peter Tiňo , Mark Girolami
关键词: Data mining 、 Generalization 、 Probability distribution 、 Exponential family 、 Manifold 、 Data visualization 、 Multidimensional analysis 、 Visualization 、 Multivariate statistics 、 Knowledge representation and reasoning 、 Interactive visualization 、 Data point 、 Computer science
摘要: We present a general framework for interactive visualization and analysis of multi-dimensional data points. The proposed model is hierarchical extension the latent trait family models developed in [4] as generalization GTM to noise from exponential distributions. As some members distributions are suitable modeling discrete observations, we give brief example using our methodology semantic discovery corpus text-based documents. also derive formulas computing local magnification factors projection manifolds.
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sci-hub.st 参考文章(13)
Teuvo Kohonen, Self-organized formation of topologically correct feature maps Biological Cybernetics. ,vol. 43, pp. 509- 521 ,(1988) , 10.1007/BF00337288
Mehran Sahami, Daphne Koller, Using machine learning to improve information access Stanford University. ,(1998)
Peter McCullagh, John Ashworth Nelder, Generalized Linear Models ,(1983)
Markus Svens'en, Christopher K. I. Williams, Christopher M. Bishop, Magnification factors for the SOM and GTM algorithms ,(1997)
RISTO MUKKULAINEN, None, Script Recognition with Hierarchical Feature Maps Connection Science. ,vol. 2, pp. 83- 101 ,(1990) , 10.1080/09540099008915664
Christopher M Bishop, Markus Svensén, Christopher KI Williams, Magnification factors for the GTM algorithm Fifth International Conference on Artificial Neural Networks. pp. 64- 69 ,(1997) , 10.1049/CP:19970703
Michael I Jordan, Robert A Jacobs, None, Hierarchical mixtures of experts and the EM algorithm Neural Computation. ,vol. 6, pp. 181- 214 ,(1994) , 10.1162/NECO.1994.6.2.181
A. Kaban, M. Girolami, A combined latent class and trait model for the analysis and visualization of discrete data IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 23, pp. 859- 872 ,(2001) , 10.1109/34.946989
C.M. Bishop, M.E. Tipping, A hierarchical latent variable model for data visualization IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 20, pp. 281- 293 ,(1998) , 10.1109/34.667885
P. Tino, I. Nabney, Hierarchical GTM: constructing localized nonlinear projection manifolds in a principled way IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 24, pp. 639- 656 ,(2002) , 10.1109/34.1000238