Geodesic
The method of machine learning based on graphical data
Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Kazanskii Gosudarstvennyi Universitet. Uchenye Zapiski. Seriya Fiziko-Matematichaskie Nauki, Tome 149 (2007) no. 2, pp. 92-104 Cet article a éte moissonné depuis la source Math-Net.Ru

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This paper is devoted to a new method of machine learning based on graphical data (named FuzGraph). The method is founded on fuzzy representation of graphical data. Set of samples of similar images on the figure $y=f(x)$ are described as combination of fuzzy functions. These functions are results of fuzzification of density of probability of some geometric parameters of the revealed images. The method is convenient for detection of laws on the graphical data having the stochastic nature. Testing and approbation of the method were passed on the problem of forecasting of the prices of currencies and stocks in a figure “flag”, which is actual for the financial markets. 
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E. N. Leonov; V. N. Polyakov. The method of machine learning based on graphical data. Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Kazanskii Gosudarstvennyi Universitet. Uchenye Zapiski. Seriya Fiziko-Matematichaskie Nauki, Tome 149 (2007) no. 2, pp. 92-104. http://geodesic.mathdoc.fr/item/UZKU_2007_149_2_a5/

[1] Samuel A., “Some Studies in Machine Learning Using the Game of Checkers”, IDM J. Research and Development, 1959, no. 3, 211–229 | MR

[2] Nilsson Nils. J., Introduction to Machine Learning [Elektronnyi resurs], Stanford University 1996., Stanford, CA, Rezhim dostupa svobodnyi http://www.robotics.stanford.edu/ people/nilsson/mlbook.html

[3] Carbonell J. G., “Learning by analogy: Formulating and generalizing plans from past experience”, Machine Learning: An Artificial Intelligence Approch, eds. R. Michalski , J. Carbonell, T. Mitchell, Tioga Publishing Co., Palo Alto, CA, 1983, 137–161

[4] Kolodner J., Case-Based Reasoning, Morgan Kaufmann Publ., San Mateo, CA, 1993, 668 pp.

[5] McCulloch W. S., Pitts W. H., “A Logical Calculus of the Ideas Immanent in Nervous Activity”, Bulletin of Mathematical Biophysics, v. 5, University of Chicago Press, Chicago, 1943, 115–133 | DOI | MR

[6] Holland J. H., Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, MI, 1975, 183 pp. | MR

[7] DeJong G., Mooney R., “Explanation-Based Learning: An Alternative View”, Machine Learning, 1968, no. 1, 145–176; Shavlik J., Dietterich T., Reprinted, Readings in Machine Learning, Morgan Kaufmann, San Francisco, 1990, 452–467

[8] Koza J., Genetic Programming: On the programming of Computers by Means of Natural Selection, MIT Press, Cambridge, 1992, 840 pp. | Zbl

[9] Koza J., Genetic Programming. II. Automatic Discovery of Reusable programs, MIT Press, Cambridge, 1994, 746 pp. | Zbl

[10] Elder A., Kak igrat i vyigryvat na birzhe, Izd. dom “KRON-press”, M., 1996, 332 pp.

[11] Averkin A. N., Batyrshin I. Z., Blishun A. F., Silov V. B., Tarasov V. B., Nechetkie mnozhestva v modelyakh upravleniya i iskusstvennogo intellekta, ed. D. A. Pospelov, Nauka, M., 1986, 312 pp. | Zbl

[12] Polyakov V., Shevchenko A., “Tekhnologiya prinyatiya reshenii na valyutnykh i fondovykh rynkakh s ispolzovaniem nechetkoznachnoi modeli figury “flag””, Tr. vosmoi nats. konf. po iskusstvennomu intellektu (KII-2002) (Kolomna, Rossiya, 7–12 okt. 2002 g.), v. 1, Fizmatlit, M., 2002, 343–352