visualizing Data using t-SNE: Difference between revisions
Jump to navigation
Jump to search
(Created page with '=Introduction= =Stochastic Neighbor Embedding= =t-Distributed Stochastic Neighbor Embedding= == Symmetric SNE == == The Crowding Problem == == Compensating for Mismatched ...') |
|||
Line 1: | Line 1: | ||
=Introduction= | =Introduction= | ||
The paper <ref>Laurens van der Maaten, and Geoffrey Hinton, 2008. Visualizing Data using t-SNE.</ref> introduced a new nonlinear dimensionally reduction technique that visualizes high-dimensional data based on the pair-wise similarities between the datapoints. This technique is a variation of the Stochastic Neighbor embedding that was proposed by Hinton and Roweis <ref>G.E. Hinton and S.T. Roweis, 2002. Stochastic Neighbor embedding.</ref>. | |||
=Stochastic Neighbor Embedding= | =Stochastic Neighbor Embedding= |
Revision as of 15:44, 12 July 2009
Introduction
The paper <ref>Laurens van der Maaten, and Geoffrey Hinton, 2008. Visualizing Data using t-SNE.</ref> introduced a new nonlinear dimensionally reduction technique that visualizes high-dimensional data based on the pair-wise similarities between the datapoints. This technique is a variation of the Stochastic Neighbor embedding that was proposed by Hinton and Roweis <ref>G.E. Hinton and S.T. Roweis, 2002. Stochastic Neighbor embedding.</ref>.