Chapter 15 References
·
Fayyad U., Grinstein G., and Wierse A., Eds., Information
Visualization in Data Mining and Knowledge Discovery, Morgan-Kaufman, 2001.
·
Keim D., Visual Exploration of Large Data Sets, Communication of
ACM, vol. 44, N.8, 2001, pp. 39-44.
·
Keeney R.L., Raiffa H. Decisions with Multiple Objectives:
preferences and value Tradeoffs. John Wiley& Sons, 1976
·
Krantz DH, Luce RD, Suppes P, Tversky A: Foundations of
Measurement v.1-3, Acad. Press, NY, London. 1971, 1989, 1990.
·
Kuakov Yu.I. The One Principal Underlying Classical Physics,
Soviet Physics – Doclagy, V.15, #7, Jan., 1971, 666-668.
·
Kovalerchuk, B., Vityaev, E. Data Mining in Finance: Advances in
Relational and Hybrid Methods, Kluwer Acad. Publ., Boston, 2000.
·
Mikhailichenko G.G. Phenomenological and Group Symmetry in the
Geometry of two Sets (Theory of Physical Structures), Soviet Math. Docl. 32(2),
1985, 371-374.
·
Mikhailichenko G.G. Solution of functional equations in the theory
of physical structures, Doklady, Soviet Academy of Sciences, 1972,
v
206, N.5
1056-1058.
·
Mille, H. (Ed) Geographic Data Mining & Knowledge Discovery,
Taylor and Francis, 2001
·
Rao H., Rao V., C++ Neural Networks and Fuzzy Logic, Hungry Minds,
Inc, 1995.
·
Soukup T., Davidson I., Visual Data Mining: Techniques and Tools
for Data Visualization and Mining, Wiley, 2002
·
Spence R., Information Visualization, Addison-Wesley, 2001.
·
Vityaev E.E. Numerical, algebraic, and constructive representation
of one physical structure. In: Logical foundations MOZ (Methods for discovery of
regularities), Computer systems, #107, Novosibirsk, 1985, pp.40-51 (in Russian).
·
Ware C. Information Visualization: perception for Design, Acad.
Press, 2000.