Comments (2)
This is wrong. The dataset should be converted internally if it's not a ml-matrix object.
@JeffersonH44 you should be able to use Matrix.checkMatrix for this purpose.
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But I'm seeing the code now and there is no need of the ml-matrix because the algorithm check if the dataset is instance of matrix I just forget it, I will change the doc.
from pca.
Related Issues (20)
- Crashes when a feature variance is 0 HOT 5
- Noob question: How do I project my data into the PCA space? HOT 3
- number of components ? HOT 4
- Mono dimensional arrays: TypeError: First argument must be a positive number or an array HOT 8
- update readme once Matrix has a custom inspect function
- Optimize predictions when nComponents is specified
- Feature Labels HOT 2
- Scores HOT 1
- How to use `getExplainedVariance` results? HOT 3
- Reference to the feature names in getExplainedVariance HOT 1
- Add Reconstructed loadings HOT 1
- NIPALS returns nans HOT 1
- Question - Plotting Ability HOT 3
- Migrate project to typescript
- Test
- fix DOI in citation.md once published on Zenodo
- RangeError: Submatrix indices are out of range HOT 4
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- Mixed ES6 and CJS causes issues in some enviroments HOT 8
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