| Autor: |
Hernandez-Mazariegos, Rodrigo, Ortiz-Bejar, Jose, Ortiz-Bejar, Jesus |
| Předmět: |
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| Zdroj: |
Engineering Proceedings; 2023, Vol. 39, p71, 9p |
| Abstrakt: |
This study compares three methods for optimizing the hyper-parameters m (embedding dimension) and τ (time delay) from Taken's Theorem for time-series forecasting to train a Support Vector Regression system (SVR). Firstly, we use a method which utilizes Mutual Information for optimizing τ and a technique referred to as "Dimension Congruence" to optimize m. Secondly, we employ a grid search and random search, combined with a cross-validation scheme, to optimize m and τ hyper-parameters. Lastly, various real-world time series are used to analyze the three proposed strategies. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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