On full regression decision trees

I. E. Genrikhov; E. V. Djukova; V. I. Zhuravlev

doi:10.1134/S1054661817010047

On full regression decision trees

Authors: Genrikhov I.E.¹, Djukova E.V.², Zhuravlev V.I.³
Affiliations:
1. LLC Mobile Park IT
2. FRC “Computer Science and Control,”
3. Moscow State University
Issue: Vol 27, No 1 (2017)
Pages: 1-7
Section: Mathematical Method in Pattern Recognition
URL: https://bakhtiniada.ru/1054-6618/article/view/194976
DOI: https://doi.org/10.1134/S1054661817010047
ID: 194976

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Abstract

One of the central problems of machine learning is considered—the regression restoration problem. A qualitatively new regression decision tree (RDT) is proposed that is based on the concept of a full decision tree (FDT). Earlier, a similar construction of a decision tree (DT) was successfully tested on the problem of classification by precedents, whose statement is close to the problem considered. The results of testing the model of a full RDT (FRDT) on real data are presented.