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01-07-2019 | APPLIED PROBLEMS | Issue 3/2019

Pattern Recognition and Image Analysis 3/2019

About methods of Synthesis Complete Regression Decision Trees

Journal:
Pattern Recognition and Image Analysis > Issue 3/2019
Authors:
I. E. Genrikhov, E. V. Djukova
Important notes
https://static-content.springer.com/image/art%3A10.1134%2FS1054661819030040/MediaObjects/11493_2019_6013_Fig5_HTML.gif
Genrikhov Igor’ Evgen’evich, born in 1985, graduated from mathematical faculty of Moscow Pedagogical Institute, since 2013 candidate of physical and mathematical sciences, now programmer of Mobile Park Ltd. He is the author of 18 publications. Fields of scientific interests: theoretical information science, discrete mathematics, pattern recognition, logical recognition procedures, heterogeneous computing.
https://static-content.springer.com/image/art%3A10.1134%2FS1054661819030040/MediaObjects/11493_2019_6013_Fig6_HTML.gif
Djukova Elena Vsevolodovna, born in 1945, graduated from Mechanical and Mathematical Faculty of Moscow State University in 1967, since 1996 doctor of physical and mathematical sciences, now the chief scientist of Federal Research Center “Computer Science and Control.” She is the author of more than 100 publications. Fields of scientific interests: logical data analysis, pattern recognition, discrete mathematics, logical recognition procedures, computational complexity of the discrete problems and synthesis of asymptotically optimal algorithms for solving the discrete problems
Translated by Yu. Zikeeva
Abstract—Algorithms for regression problem on the basis of complete decision trees are examined in the paper. The examined structure of the decision tree makes it possible to consider all features meeting the branching criterion in each special vertex of the tree. New algorithms for synthesizing complete regression decisions trees are presented. The developed algorithms are tested on real problems and it is revealed that the algorithms are efficient.

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