iVisClassifier: An interactive visual analytics system for classification based on supervised dimension reduction

VAST 10 - IEEE Conference on Visual Analytics Science and Technology 2010, Proceedings

Volumn , Issue , 2010, Pages 27-34

  Choo, Jaegul ^a   Lee, Hanseung ^b   Kihm, Jaeyeon ^a   Park, Haesun ^a  

^a Georgia Institute of Technology   (United States)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

H.5.2 information interfaces and presentation : user interfaces theory and methods

Indexed keywords

BASIS VECTOR; CLASSIFICATION TASKS; CLUSTER CENTROIDS; CLUSTER STRUCTURE; DATA DOMAINS; DIMENSION REDUCTION; DIMENSION REDUCTION METHOD; FACIAL IMAGES; HIGH DIMENSIONAL DATA; INTERACTIVITY; INTERPRETABILITY; LINEAR DISCRIMINANT ANALYSIS; PAIRWISE DISTANCES; PARALLEL COORDINATES; REDUCED DIMENSIONAL SPACE; REDUCED-DIMENSIONAL; SCATTER PLOTS; THEORY AND METHODS; VISUAL ANALYTICS;

DISCRIMINANT ANALYSIS; GRAPHICAL USER INTERFACES;

VISUALIZATION;

EID: 78650936017     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/VAST.2010.5652443     Document Type: Conference Paper

References (29)

1. M. Ankerst, C. Elsen, M. Ester, and H.-P. Kriegel. Visual classification: an interactive approach to decision tree construction. In KDD '99: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 392-396, New York, NY, USA, 1999. ACM.
2. M. Ankerst, M. Ester, and H.-P. Kriegel. Towards an effective cooperation of the user and the computer for classification. In KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 179-188, New York, NY, USA, 2000. ACM.
3. M. Ankerst, D. Keim, and H. Kriegel. 'Circle Segments': A Technique for Visually Exploring Large Multidimensional Data Sets. In Proc. Visualization, Hot Topic Session,, 1996.
4. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19:711-720, 1997.
5. K. Chen and L. Liu. ivibrate: Interactive visualization-based framework for clustering large datasets. ACM Trans. Inf. Syst., 24(2):245-294, 2006.
6. J. Choo, S. Bohn, and H. Park. Two-stage framework for visualization of clustered high dimensional data. In IEEE Symposiu on Visual Analytics Science and Technology, 2009. VAST 2009., pages 67 -74, oct. 2009.
7. R. O. Duda, P. E. Hart, and D. G. Stork. Pattern Classification. Wiley-interscience, New York, 2001.
8. J. H. Friedman. Regularized discriminant analysis. Journal of the American Statistical Association, 84(405):165-175, 1989.
9. K. Fukunaga. Introduction to Statistical Pattern Recognition, second edition. Academic Press, Boston, 1990.
10. M. Grgic, K. Delac, and S. Grgic. SCface - surveillance cameras face database. Multimedia Tools and Applications Journal, 2009.
11. P. Howland and H. Park. Generalizing discriminant analysis using the generalized singular value decomposition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(8):995-1006, aug. 2004.
12. M. Jeon, H. Park, and J. B. Rosen. Dimensional reduction based on centroids and least squares for efficient processing of text data. In Proceedings of the First SIAMInternationalWorkshop on TextMining. Chiago, IL, 2001.
13. D. Jeong, C. Ziemkiewicz, B. Fisher, W. Ribarsky, and R. Chang. iPCA: An Interactive System for PCA-based Visual Analytics. Computer Graphics Forum, 28(3):767-774, 2009.
14. S. Johansson and J. Johansson. Interactive dimensionality reduction through user-defined combinations of quality metrics. IEEE Transactions on Visualization and Computer Graphics, 15:993-1000, 2009.
15. E. Kandogan. Visualizing multi-dimensional clusters, trends, and outliers using star coordinates. In KDD '01: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, pages 107-116, New York, NY, USA, 2001. ACM.
16. H. Park, B. Drake, S. Lee, and C. Park. Fast Linear Discriminant Analysis using QR Decomposition and Regularization. Technical Report GT-CSE-07-21, 2007.
17. E. Pisano, S. Zong, B. Hemminger, M. DeLuca, R. Johnston, K. Muller, M. Braeuning, and S. Pizer. Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms. Journal of Digital Imaging, 11(4):193-200, 1998.
18. S. T. Roweis and L. K. Saul. Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science, 290(5500):2323-2326, 2000.
19. J. Seo and B. Shneiderman. Interactively exploring hierarchical clustering results [gene identification]. Computer, 35(7):80-86, jul 2002.
20. K. Y. Tam and M. Y. Kiang. Managerial Applications of Neural Networks: The Case of Bank Failure Predictions. MANAGEMENT SCIENCE, 38(7):926-947, 1992.
21. J. B. Tenenbaum, V. d. Silva, and J. C. Langford. A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science, 290(5500):2319-2323, 2000.
22. S. Teoh and K. Ma. StarClass: Interactive visual classification using star coordinates. In Proceedings of the 2003 SIAM International Conference on Data Mining (SDM03), 2003.
23. M. Turk and A. Pentland. Eigenfaces for recognition. Journal of cognitive neuroscience, 3(1):71-86, 1991.
24. L. van derMaaten and G. Hinton. Visualizing data using t-SNE. Journal of Machine Learning Research, 9:2579-2605, 2008.
25. M. Vasilescu and D. Terzopoulos. Multilinear Analysis of Image Ensembles: TensorFaces. Necture Notes in Computer Science, pages 447-460, 2002.
26. M.Williams and T.Munzner. Steerable, progressive multidimensional scaling. In Information Visualization, 2004. INFOVIS 2004. IEEE Symposium on, pages 57 -64, 0-0 2004.
27. R. Willing. Airport anti-terror systems flub tests; Face-recognition technology fails to flag "suspects". USA TODAY, September 2, 2003. Available at http://www.usatoday.com/travel/news/2003/09/02-air-secur.htm.
28. J. Yang, W. Peng, M. Ward, and E. Rundensteiner. Interactive hierarchical dimension ordering, spacing and filtering for exploration of high dimensional datasets. In Information Visualization, 2003. INFOVIS 2003. IEEE Symposium on, pages 105 -112, 21-21 2003.
29. J. Yang, M. O. Ward, E. A. Rundensteiner, and S. Huang. Visual hierarchical dimension reduction for exploration of high dimensional datasets. In VISSYM '03: Proceedings of the symposium on Data visualisation 2003, pages 19-28, Aire-la-Ville, Switzerland, Switzerland, 2003. Eurographics Association.