Julia port of L.J.P. van der Maaten and G.E. Hintons T-SNE visualisation technique.
112 Stars
Updated Last
2 Years Ago
Started In
November 2013

t-SNE (t-Stochastic Neighbor Embedding)

Julia 0.6 Status Julia 0.7 Status

Build Status Coverage Status

Julia implementation of L.J.P. van der Maaten and G.E. Hintons t-SNE visualisation technique.

The scripts in the examples folder require Plots, MLDatasets and RDatasets Julia packages.


julia> Pkg.add("TSne")

Basic API usage

using TSne, Statistics, MLDatasets

rescale(A; dims=1) = (A .- mean(A, dims=dims)) ./ max.(std(A, dims=dims), eps())

alldata, allabels = MNIST.traindata(Float64);
data = reshape(permutedims(alldata[:, :, 1:2500], (3, 1, 2)),
               2500, size(alldata, 1)*size(alldata, 2));
# Normalize the data, this should be done if there are large scale differences in the dataset
X = rescale(data, dims=1);

Y = tsne(X, 2, 50, 1000, 20.0);

using Plots
theplot = scatter(Y[:,1], Y[:,2], marker=(2,2,:auto,stroke(0)), color=Int.(allabels[1:size(Y,1)]))
Plots.pdf(theplot, "myplot.pdf")

Command line usage

julia demo-csv.jl haveheader --labelcol=5 iris-headers.csv

Creates myplot.pdf with t-SNE result visualized using Gadfly.jl.

See also

Used By Packages