DATASET PCA (TRANSFORM)¶
Applies a previously-fitted PCA projection (parameters from dataset_pca_fit) to a new dataset WITHOUT refitting, appending the principal-component score columns. Columns absent from the new dataset are treated as the training mean (standardized 0), so a testing set with fewer/shorter curve columns than training is tolerated.
When to use¶
Tagged: pca, dimensionality_reduction, transform, apply, train_test, curves.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Dataset | dataset | dataset | — | ✓ | Testing/new dataset to project using the saved PCA; array-of-row-objects. |
| PCA Parameters | pca_parameters | json | — | ✓ | PCA parameters object produced by dataset_pca_fit (components, mean, std, columns, pc_prefix). |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| Dataset With PCs | dataset | dataset | Input dataset with appended PC score columns from the saved projection. |
| Status | status | string | Summary including any columns treated as training mean. |
Disciplines¶
- data.dataset.transform
- data.statistics
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