Обзор развития алгоритмов деревьев решений

Социология: методология, методы, математическое моделирование. 2020. Т. 0. № 50-51. С. 63–96.

Suleimanova A.

Decision trees are a method of classification and prediction, widely applied in sociological research. It is unchangingly popular due to its flexibility and simplicity of interpretation. Choosing the most appropriate decision tree algorithm is not an easy task for several reasons: (a) there is already over a hundred algorithms with different strengths, weaknesses and logic of growth, (b) literature on the topic is fragmented and optimized versions of existing algorithms are often presented as entirely new types of trees and (c) the statistical software is equally as fragmented as literature. As a result, researchers often apply algorithms that are available in their preferred statistical package or rely on one of the old, imperfect methods. The review aims to reveal and describe decision tree algorithms and their application, discussed over the last five years. Bibliographic analysis and a network of keywords are applied to reveal the path of current scientific discussion on the topic.

Keywords: деревья решений, деревья классификации, большие данные, decision trees, big data, classification trees, regression trees, bibliographic analysis, библиографический анализ, Деревья регрессии