Communications in Computer and Information Science, volume 1488 CCIS, pages 72-85
Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models
Publication type: Book Chapter
Publication date: 2021-12-02
Quartile SCImago
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Impact factor: —
ISSN: 18650929
Abstract
In modern data science, it is often not enough to obtain only a data-driven model with a good prediction quality. On the contrary, it is more interesting to understand the properties of the model, which parts could be replaced to obtain better results. Such questions are unified under machine learning interpretability questions, which could be considered one of the area’s raising topics. In the paper, we use multi-objective evolutionary optimization for composite data-driven model learning to obtain the algorithm’s desired properties. It means that whereas one of the apparent objectives is precision, the other could be chosen as the complexity of the model, robustness, and many others. The method application is shown on examples of multi-objective learning of composite models, differential equations, and closed-form algebraic expressions are unified and form approach for model-agnostic learning of the interpretable models.
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Hvatov A. et al. Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models // Communications in Computer and Information Science. 2021. Vol. 1488 CCIS. pp. 72-85.
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Hvatov A., Maslyaev M., Polonskaya I. S., Sarafanov M., Merezhnikov M., Nikitin N. O. Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models // Communications in Computer and Information Science. 2021. Vol. 1488 CCIS. pp. 72-85.
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TY - GENERIC
DO - 10.1007/978-3-030-91885-9_6
UR - https://doi.org/10.1007%2F978-3-030-91885-9_6
TI - Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models
T2 - Communications in Computer and Information Science
AU - Hvatov, Alexander
AU - Maslyaev, Mikhail
AU - Polonskaya, Iana S
AU - Sarafanov, Mikhail
AU - Merezhnikov, Mark
AU - Nikitin, Nikolay O
PY - 2021
DA - 2021/12/02 00:00:00
PB - Springer Nature
SP - 72-85
VL - 1488 CCIS
SN - 1865-0929
ER -
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@incollection{2021_Hvatov,
author = {Alexander Hvatov and Mikhail Maslyaev and Iana S Polonskaya and Mikhail Sarafanov and Mark Merezhnikov and Nikolay O Nikitin},
title = {Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models},
publisher = {Springer Nature},
year = {2021},
volume = {1488 CCIS},
pages = {72--85},
month = {dec}
}