Manifold Learning

Isomap/LocallyLinearEmbedding/MDS/SpectralEmbedding/TSNE

Common

Input Data

	Inputs
*Target Data(X)	Data Input
*Model Name	Name of the user-defined manifold learning model
Transform	If not empty, the reduced 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 TSNE]

Workflow Example

Python Package

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

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

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

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

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