Non linear PCA and the benefits over linear PCA
The increasingly complex world revolves around data with often high dimensionality. To combat this issue, Principal Component Analysis (PCA) aims to reduce the dimension of the problem to sieve out the most important combinations of random variables which account for the highest variance of the prob...
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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/10356/184477 |
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