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rcluster-analysisdimensionality-reductionmds

what is the tsne initial pca step doing

Looking at the parameters to the Rtsne function:

https://cran.r-project.org/web/packages/Rtsne/Rtsne.pdf

There is a parameter called "pca" defined as "logical; Whether an initial PCA step should be performed (default: TRUE)"

Let's say you have a 10 dimensional feature set and you run TSNE. I was thinking you would scale the 10-D matrix and then pass it to Rtsne().

What does the pca indicated by the pca parameter do?

WOuld it take the 10-D matrix and run PCA on that? If so, would it pass all 10 dimensions in the PCA space to Rtsne?

Is there any info anywhere else about what this initial PCA step is?

Thank you.

Solution

  • The original tSNE paper used PCA.

    To reduce the dimensionality of the MNIST data prior to running tSNE.