Multi-Objective Evolutionary Design of Composite Data-Driven Models

Polonskaia I.S., Nikitin N.O., Revin I., Vychuzhanin P., Kalyuzhnaya A.V.
Тип документаProceedings Article
Дата публикации2021-01-01
Название журнала2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
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Краткое описание
In this paper, a multi-objective approach for the design of composite data-driven mathematical models is proposed. It allows automating the identification of graph-based heterogeneous pipelines that consist of different blocks: machine learning models, data preprocessing blocks, etc. The implemented approach is based on a parameter-free genetic algorithm (GA) for model design called GPComp@Free. It is developed to be part of automated machine learning solutions and to increase the efficiency of the modeling pipeline automation. A set of experiments was conducted to verify the correctness and efficiency of the proposed approach and substantiate the selected solutions. The experimental results confirm that a multi-objective approach to the model design allows us to achieve better diversity and quality of obtained models. The implemented approach is available as a part of the open-source AutoML framework FEDOT.
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1. Polonskaia I. S. и др. Multi-Objective Evolutionary Design of Composite Data-Driven Models // 2021 IEEE Congress on Evolutionary Computation (CEC). 2021.
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TY - CPAPER

DO - 10.1109/cec45853.2021.9504773

UR - http://dx.doi.org/10.1109/CEC45853.2021.9504773

TI - Multi-Objective Evolutionary Design of Composite Data-Driven Models

T2 - 2021 IEEE Congress on Evolutionary Computation (CEC)

AU - Polonskaia, Iana S.

AU - Nikitin, Nikolay O.

AU - Revin, Ilia

AU - Vychuzhanin, Pavel

AU - Kalyuzhnaya, Anna V.

PY - 2021

DA - 2021/06/28

PB - IEEE

ER -

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@inproceedings{Polonskaia_2021,

doi = {10.1109/cec45853.2021.9504773},

url = {https://doi.org/10.1109%2Fcec45853.2021.9504773},

year = 2021,

month = {jun},

publisher = {{IEEE}},

author = {Iana S. Polonskaia and Nikolay O. Nikitin and Ilia Revin and Pavel Vychuzhanin and Anna V. Kalyuzhnaya},

title = {Multi-Objective Evolutionary Design of Composite Data-Driven Models},

booktitle = {2021 {IEEE} Congress on Evolutionary Computation ({CEC})}

}

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Polonskaia, Iana S., et al. “Multi-Objective Evolutionary Design of Composite Data-Driven Models.” 2021 IEEE Congress on Evolutionary Computation (CEC), June 2021. Crossref, https://doi.org/10.1109/cec45853.2021.9504773.