Have a personal or library account? Click to login
Can interestingness measures be usefully visualized? Cover
Open Access
|Jun 2015

References

  1. Agrawal, R., Imielinski, T. and Swami, A. (1993). Mining associations between sets of items in massive databases, Proceedings of the 1993 ACM-SIGMOD International Conference on Management of Data, Washington, DC, USA, pp. 207-216.
  2. Alaíz-Rodríguez, R., Japkowicz, N. and Tischer, P.E. (2008). Visualizing classifier performance on different domains, ICTAI 2008, Dayton, OH, USA, pp. 3-10.
  3. Carnap, R. (1962). Logical Foundations of Probability, 2nd Edn., University of Chicago Press, Chicago, IL.
  4. Christensen, D. (1999). Measuring confirmation, Journal of Philosophy 96(9): 437-461.10.2307/2564707
  5. Crupi, V., Tentori, K. and Gonzalez, M. (2007). On Bayesian measures of evidential support: Theoretical and empirical issues, Philosophy of Science 74(2): 229-252.10.1086/520779
  6. Drummond, C. and Holte, R.C. (2006). Cost curves: An improved method for visualizing classifier performance, Machine Learning 65(1): 95-130.10.1007/s10994-006-8199-5
  7. Eells, E. (1982). Rational Decision and Causality, Cambridge University Press, Cambridge.10.1017/CBO9781316534823
  8. Everson, R.M. and Fieldsend, J.E. (2006). Multi-class ROC analysis from a multi-objective optimisation perspective, Pattern Recognition Letters 27(8): 918-927.10.1016/j.patrec.2005.10.016
  9. Fitelson, B. (1999). The plurality of Bayesian measures of confirmation and the problem of measure sensitivity, Philosophy of Science 66: 362-378.10.1086/392738
  10. Fitelson, B. (2001). Studies in Bayesian Confirmation Theory, Ph.D. thesis, University of Wisconsin, Madison, WI.
  11. Floater, M.S., Hormann, K. and Kos, G. (2006). A general construction of barycentric coordinates over convex polygons, Advances in Computational Mathematics 24(1-4): 311-331.10.1007/s10444-004-7611-6
  12. Fukuda, T., Morimoto, Y., Morishita, S. and Tokuyama, T. (1996). Data mining using two-dimensional optimized association rules: Scheme, algorithms, and visualization, Proceedings of the 1996 ACM-SIGMOD International Conference on the Management of Data, Montreal, Quebec, Canada, pp. 13-23.
  13. Geng, L. and Hamilton, H. (2006). Interestingness measures for data mining: A survey, ACM Computing Surveys 38(3), Article no. 9.
  14. Greco, S., Pawlak, Z. and Słowi´nski, R. (2004). Can Bayesian confirmation measures be useful for rough set decision rules?, Engineering Applications of Artificial Intelligence 17(4): 345-361.10.1016/j.engappai.2004.04.008
  15. Greco, S., Słowi´nski, R. and Szcz˛ech, I. (2012). Properties of rule interestingness measures and alternative approaches to normalization of measures, Information Sciences 216: 1-16.10.1016/j.ins.2012.05.018
  16. Healey, C. (1996). Choosing effective colors for data visualization, Proceedings of the 7th Conference on Visualization, VIS’96, San Francisco, CA, USA, pp. 263-270.
  17. Hernández-Orallo, J., Flach, P.A. and Ramirez, C.F. (2011). Brier curves: A new cost-based visualisation of classifier performance, Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, WA, USA, pp. 585-592.
  18. IBM (1996). Intelligent miner user guide, Version 1, Release 1, Technical report, International Business Machines, San Jose, CA. Kemeny, J. and Oppenheim, P. (1952). Degrees of factual support, Philosophy of Science 19(4): 307-324.
  19. Mortimer, H. (1988). The Logic of Induction, Prentice Hall, Paramus, NJ.
  20. Morzy, T. and Zakrzewicz, M. (2003). Data mining, in J. Blazewicz,W. Kubiak, T.Morzy and M.E. Rusinkiewicz (Eds.), Handbook on Data Management Information Systems, Springer, Heidelberg, pp. 487-565.10.1007/978-3-540-24742-5_11
  21. Nozick, R. (1981). Philosophical Explanations, Clarendon Press, Oxford.
  22. Pawlak, Z. (2002). Rough sets, decision algorithms and Bayes’ theorem, European Journal of Operational Research 136(1): 181-189.10.1016/S0377-2217(01)00029-7
  23. Pawlak, Z. (2004). Some issues on rough sets, Transactions on Rough Sets I, Elsevier Science Publishers, New York, NY, pp. 1-58.
  24. Shaikh, M., McNicholas, P.D., Antonie, M.L. and Murphy, T.B. (2013). Standardizing interestingness measures for association rules, Computing Research Repository, http://arxiv.org/abs/1308.3740.
  25. Susmaga, R. and Szcz˛ech, I. (2013). Visualization of interestingness measures, Proceedings of the 6th Language & Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics, Poznań, Poland, pp. 95-99.
  26. Susmaga, R. and Szcz˛ech, I. (2014). Visual-based detection of properties of confirmation measures, in T. Andreasen, H. Christiansen, J.C.C. Talavera and Z.W. Ras (Eds.), Proceedings of the 21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014, Lecture Notes in Computer Science, Vol. 8502, Springer, Heidelberg, pp. 133-143.10.1007/978-3-319-08326-1_14
  27. Tan, P., Kumar, V. and Srivastava, J. (2002). Selecting the right interestingness measure for association patterns, Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Edmonton, Alberta, Canada, pp. 32-41.
  28. Ware, C. (2004). Information Visualization: Perception for Design, 2nd Edition, Morgan Kaufmann, Waltham, MA.
  29. Warren, J. (2003). On the uniqueness of barycentric coordinates, in R. Goldman and R. Krasauskas (Eds.), Topics in Algebraic Geometry and Geometric Modeling, Contemporary Mathematics, Vol. 334, American Mathematical Society, Providence, RI, USA, pp. 93-99.10.1090/conm/334/05977
  30. Zhou, Y., Wischgoll, T., Blaha, L.M., Smith, R. and Vickery, R.J. (2014). Visualizing confusion matrices for multidimensional signal detection correlational methods, Proceedings of the SPIE Conference on Visualization and Data Analysis, San Francisco, CA. 10.1117/12.2042610
DOI: https://doi.org/10.1515/amcs-2015-0025 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 323 - 336
Submitted on: Mar 11, 2014
Published on: Jun 25, 2015
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Robert Susmaga, Izabela Szczęch, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.