Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: International Workshop “Hybrid methods of modeling and optimization in complex systems” (HMMOCS 2022); Krasnoyarsk; Krasnoyarsk
Год издания: 2022
Идентификатор DOI: 10.15405/epct.23021.14
Ключевые слова: decision trees, genetic programming algorithm, composition of algorithms, differential evolution
Аннотация: Decision trees are an efficient data analysis tool. Ensembling methods have been developed on the basis of decision trees. These methods make it possible to obtain a data analysis tool in the form of a composition of trees. The paper proposes a new approach since the development of compositions based on decision trees is an urgent Показать полностьюproblem. The paper proposes a new hybrid approach to designing the composition of decision trees. The approach is based on the idea of the decision tree application built by a genetic programming algorithm as a technique to determine a machine learning method for object classification. Thus, with the help of the proposed approach the authors carry out a hybridization of a self-configuring genetic programming algorithm and a decision tree. The paper treats decision trees built by a modified algorithm with differential evolution considered as data analysis methods that make decisions concerning a sample objects classification. The proposed method is studied on some classification problems with different types of data and dimensions. The comparison with other methods for building compositions of decision trees is made.
Журнал: HYBRID METHODS OF MODELING AND OPTIMIZATION IN COMPLEX SYSTEMS
Номера страниц: 111-116
Место издания: London, United Kingdom
Издатель: European Proceedings