On full regression decision trees
I. E. Genrikhov, E. V. Djukova, Vladimir I. Zhuravlev · Pattern Recognition and Image Analysis · 2017
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.