Here’s how to create a t-SNE graph in R (this is copied from the help file for Rtsne)…

[sourcecode language="R"] library("Rtsne") iris_unique <- unique(iris) # Remove duplicates iris_matrix <- as.matrix(iris_unique[,1:4]) set.seed(42) # Set a seed if you want reproducible results tsne_out <- Rtsne(iris_matrix) # Run TSNE # Show the objects in the 2D tsne representation plot(tsne_out$Y,col=iris_unique$Species) [/sourcecode]

I don’t suppose you could do another video on Locally Linear Embeddings, could you? I realize it’s similar to t-SNE, but it would be nice to have an intuitive yet substantive explanation of the similarities and differences.

Great videos, btw!

Thanks, John Strong

That’s a great idea. Someone else has already asked for me to do “isomap” dimension reduction, and Locally-linear embedding is related, so I’ll add it to the to-do list.

I just discovered you and your absolutely amazing work!!!! I wish I knew about you earlier! I was wondering if you could do UMAP too? Thank you!

GREAT VIDEOS, thank you for helping me a lot.

But I’ve got a little question.

Before I use the t-SNE to put datasets into graph, should I use PCA first to cluster the datasets?

A lot of people do that first and just apply t-SNE to the first handful of principal components.