Matrix Decomposition

FactorAnalysis/FastICA/IncrementalPCA/KernelPCA/MiniBatchSparsePCA/NMF/PCA/SparsePCA/TruncatedSVD

Common

Input Data

Inputs

*Target Data(X)

Data Input

*Model Name

Name of the user-defined matrix decomposition model

Transform

If not empty, the result matrix will be stored here.

If left empty, the model will only compute scores on individual features.

Conv.DataFrame

If checked, the output data created by Transform will be converted into a DataFrame.

*x (numeric)

User-selected columns to be X.

  • One or more columns should be selected.

Workflow Example

Python Package

FactorAnalysis: https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.FactorAnalysis.html

FastICA: https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.FastICA.html

IncrementalPCA: https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.IncrementalPCA.html

KernelPCA: https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.KernelPCA.html

MiniBatchSparsePCA: https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchSparsePCA.html

NMF: https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.NMF.html

PCA: https://scikit-learn.org/stable/modules/generated/sklearn.PCA.html

SparsePCA: https://scikit-learn.org/stable/modules/generated/sklearn.SparsePCA.html

TruncatedSVD: https://scikit-learn.org/stable/modules/generated/sklearn.TruncatedSVD.html

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