Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling

In the previous chapter, we went through a text visualization using t-SNE. t-SNE, or any dimensionality reduction algorithm, is a type of unsupervised learning. In this chapter, we will be continuing our unsupervised learning journey, specifically focusing on clustering and topic modeling. We will start with how unsupervised learning learns without guidance and how it is good at discovering hidden information underneath data.

Next, we will talk about clustering as an important branch of unsupervised learning, which identifies different groups of observations from data. For instance, clustering is useful for market segmentation, where consumers of similar behaviors are grouped into one segment for marketing purposes. We will perform clustering on the 20 newsgroups text dataset and see what clusters will be produced.

Another unsupervised learning route we will take is topic modeling, which...