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.
more than wonderful
you make statistics easier and relaxing！