7  Goal of Unsupervised Learning

TipLearning Objectives
  • Goals of unsupervised learning
  • Different ways in which unsupervised learning can be used

7.1 Goals of unsupervised learning

  • Finding patterns in data

Here is an example from biological data (single-cell sequencing data) (the plot is from [2])(Aschenbrenner et al. 2020).

Example tSNE

Example heatmaps
  • Finding interesting patterns

You can also use dimensionality reduction techniques (such as PCA) to find interesting patterns in your data.

  • Finding outliers

You can also use dimensionality reduction techniques (such as PCA) to find outliers in your data.

  • Finding hypotheses

All of these can be used to generate hypotheses. These hypotheses can be tested by collecting more data.

7.2 Thought exercise

  • Can you think of a technique where unsupervised learning gets used a lot? Hint: we use it almost every day now! (or atleast I do)

ChatGPT or Generative AI. The first step in processing the huge amount of text is to reduce the dimensions of the data using something similar to PCA.

7.3 Summary

TipKey Points
  • The goal of unsupervised learning is to find patterns and form hypotheses.