COMPARISON OF DOUBLE RANDOM FOREST AND LONG SHORT-TERM MEMORY METHODS FOR ANALYZING ECONOMIC INDICATOR DATA
The performance of machine learning in analyzing time series data is being widely discussed. A new ensemble method Double Random Forest (DRF), which considers supervised learning currently developed. This method has been claimed to be able to improve the performance of Random Forest (RF) if the data...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Pattimura
2023-06-01
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| Series: | Barekeng |
| Subjects: | |
| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7738 |
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