Applied Unsupervised Learning with Python

Chapter 6

t-Distributed Stochastic Neighbor Embedding (t-SNE)

Learning Objectives

By the end of this chapter, you will be able to:

• Describe and understand the motivation behind t-SNE
• Describe the derivation of SNE and t-SNE
• Implement t-SNE models in scikit-learn
• Explain the limitations of t-SNE

In this chapter, we will discuss Stochastic Neighbor Embedding (SNE) and t-Distributed Stochastic Neighbor Embedding (t-SNE) as a means of visualizing high-dimensional datasets.

Introduction

This chapter is the final instalment in the micro-series on dimensionality reduction techniques and transformations. Our previous chapters in this series have described a number of different methods for reducing the dimensionality of a dataset as a means of ...