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.

[Task information of AffinityPropagation]

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