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Investigation of the Importance of Input Features by Linear Regression in Predicting the Geomagnetic Index by Machine Learningстатья Исследовательская статья
- Авторы: Vladimirov Roman, Shirokii Vladimir, Barinov Oleg, Myagkova Irina, Dolenko Sergei
- Сборник: 2022 VIII International Conference on Information Technology and Nanotechnology (ITNT)
- Год издания: 2022
- Место издания: IEEE
- DOI: 10.1109/itnt55410.2022.9848686
- Аннотация: One of the most effective tools for predicting time series is the use of machine learning methods, in particular, artificial neural networks. However, at the same time, a necessary stage of the study is to reduce the dimension of the input data. In this paper, we consider the results of data dimensionality reduction based on the ranking of input features by their significance in solving the problem of forecasting the geomagnetic Dst index. To assess the relative significance of features, an iterative approach is used, associated with the search of candidate models by discarding features one by one based on simple linear regression models.
- Добавил в систему: Доленко Сергей Анатольевич