Causation versus correlation: when does it matter?
Feature engineering is a critical step in the machine learning pipeline, particularly when dealing with high-dimensional datasets where redundant or irrelevant features can degrade performance. It involves either creating new features from the existing dataset or selecting relevant features from...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2025
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| Online Access: | https://hdl.handle.net/10356/184145 |
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| Institution: | Nanyang Technological University |
| Language: | English |