Principal component analysis (PCA) is a common unsupervised learning technique that is useful for both exploratory data analysis and dimension reduction.
| Function | Description |
|---|---|
| PCA (ML Engine) | Composed of PCAMap and PCAReduce. Uses deterministic algorithm to identify principal components of input table in dense format. |
| PCAScore (ML Engine) | Takes data in dense format and projects it onto specified subset of principal components identified by PCA. |