fit-sne 1.2.1 Fast Fourier Transform-accelerated interpolation-based t-SNE

t-Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization of high dimensional datasets. A popular implementation of t-SNE uses the Barnes-Hut algorithm to approximate the gradient at each iteration of gradient descent. This implementation differs in these ways:

  • Instead of approximating the N-body simulation using Barnes-Hut, we interpolate onto an equispaced grid and use FFT to perform the convolution.

  • Instead of computing nearest neighbors using vantage-point trees, we approximate nearest neighbors using the Annoy library. The neighbor lookups are multithreaded to take advantage of machines with multiple cores.