3 Best Bokeh T-Sne

bokeh t-sne lda model with bokeh and t sneTour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site bokeh t-sne borg github io blog 2016 tsnet SNE is a very powerful technique that can be used for visualising looking for patterns in multi dimensional data Great things have been said about this technique In this blog post I did a few experiments with t SNE in R to learn about this technique and its uses

embeddingst SNE t distributed stochastic neighbour embedding is a popular algorithm in the deep learning crowd for displaying high dimensional data in 2D 3D Let s see how we can use it to display our vectors bokeh t-sne tsneHow to Use t SNE Effectively Although extremely useful for visualizing high dimensional data t SNE plots can sometimes be mysterious or misleading By exploring how it behaves in simple cases we can learn to use it more effectively play arrowpause refresh Step link Share this view nadbordrozd github io blog 2016 06 13 deepwalking with companiesPretty pictures with t SNE and Bokeh The embedding produced by DeepWalk was 100 dimensional in this case so I had to do some dimensionality reduction before trying to visualize the vectors t SNE is perfect for this kind of thing

SNE tutorialThe t SNE algorithm works around this problem by using a t Student with one degree of freedom or Cauchy distribution for the map points This distribution has a much heavier tail than the Gaussian distribution which compensates the original imbalance bokeh t-sne nadbordrozd github io blog 2016 06 13 deepwalking with companiesPretty pictures with t SNE and Bokeh The embedding produced by DeepWalk was 100 dimensional in this case so I had to do some dimensionality reduction before trying to visualize the vectors t SNE is perfect for this kind of thing PDF fileVisualizing Dynamics from t SNE to SEMI MDPs Figure 1 SMDP visualization for Breakout purpose of model selection According to this principle the best hypothesis for a given data set is the one that leads to the best compression of the data Here the goal is