Data augmentation and mixup techniques for stock returns prediction
In financial forecasting, the caliber of data underpinning models is critical for precision in predicting market trends. This research investigates the efficacy of data aug- mentation, a technique widely used in domains such as image processing, applied to financial time series. We assess how method...
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| フォーマット: | Final Year Project (FYP) |
| 言語: | English |
| 出版事項: |
Nanyang Technological University
2024
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| オンライン･アクセス: | https://hdl.handle.net/10356/175462 |