Prediction of Locally Stationary Data Using Expert Advice

• URL: http://arxiv.org/abs/2310.19591v1
• Date: Mon, 30 Oct 2023 14:48:01 GMT
• Title: Prediction of Locally Stationary Data Using Expert Advice
• Authors: Vladimir V'yugin, Vladimir Trunov
• Abstract summary: The problem of continuous machine learning is studied. No assumptions about the nature of the source that generates the data flow are used. An online forecasting algorithm for a locally stationary time series is presented.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The problem of continuous machine learning is studied. Within the framework of the game-theoretic approach, when for calculating the next forecast, no assumptions about the stochastic nature of the source that generates the data flow are used -- the source can be analog, algorithmic or probabilistic, its parameters can change at random times, when building a prognostic model, only structural assumptions are used about the nature of data generation. An online forecasting algorithm for a locally stationary time series is presented. An estimate of the efficiency of the proposed algorithm is obtained.

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