2021
DOI: 10.56947/amcs.v2.13
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Machine learning methods in time series forecasting: a review

Saidjon Kamolov,
Dilshod Iskhakov,
Bakhrom Ziyaev

Abstract: The improvements in machine learning algorithms have spurred their application in various fields. In this paper, we consider the use of machine learning in financial forecasting. Our review consists of two parts': data driven approaches and model-based solutions. We discuss state-of-the-art literature in this field and analyze future trends.

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Cited by 2 publications
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