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Principal Component Analysis
| Icon | Name | Description / Applications | Modules | |
|---|---|---|---|---|
| ApplyPCATransform | ApplyPCATransform | Applies previously obtained Principal Component Analysis (PCA) transformation coefficients to new data. |
FoundationPro | |
| CreatePCATransform | CreatePCATransform | Performs the Principal Component Analysis (PCA) on provided data, creates the feature vector and normalization coefficients (mean and standard deviation of variables). |
FoundationPro | |
| MatrixDeterminant | MatrixDeterminant | Find the determinant of a square matrix. |
FoundationPro | |
| MatrixPseudoEigenvectors | MatrixPseudoEigenvectors | Find the pseudo-eigenvalues and pseudo-eigenvectors of a symmetrical square matrix. |
FoundationPro | |
| NormalizeMatrixData | NormalizeMatrixData | Treats Matrix as a data frame, where examples are in rows while columns represent features, and normalizes the data by subtracting mean from each column and dividing it by its standard deviation. |
FoundationPro | |
| ReversePCATransform | ReversePCATransform | Reverses Principal Component Analysis (PCA) process. Can be used to transform data back to original feature space. |
FoundationPro |
