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...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2025
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/184477 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|