10.26731/2658-3704.2020.3(8).1-10
The article is devoted to the development of an algorithm for constructing high-quality and well-interpreted regression models. The analysis of the program complex for the automation of the process of constructing regression models, intended for the implementation of the "competition" of models, is performed. Based on the analysis, a number of shortcomings of this software product were identified, in particular, the fact that the regression models obtained as a result of its work are often difficult to interpret. On the basis of the identified shortcomings, the concept of "well-interpreted qualitative model" was introduced for the first time. Requirements for such regressions are formulated. An efficient algorithm "Selection B" for the implementation of the "competition" models is considered. A fundamental block of algorithms for constructing well-interpreted qualitative regression models has been developed. To implement it, it is enough to modernize the effective algorithm "Selection B".
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