Clustering newsgroups dataset

You should now be very familiar with k-means clustering. Next, let’s see what we are able to mine from the newsgroups dataset using this algorithm. We will use all the data from four categories, 'alt.atheism', 'talk.religion.misc', 'comp.graphics', and 'sci.space', as an example. We will then use ChatGPT to describe the generated newsgroup clusters. ChatGPT can generate natural language descriptions of the clusters formed by k-means clustering. This can help in understanding the characteristics and themes of each cluster.

Clustering newsgroups data using k-means

We first load the data from those newsgroups and preprocess it as we did in Chapter 7, Mining the 20 Newsgroups Dataset with Text Analysis Techniques:

>>> from sklearn.datasets import fetch_20newsgroups
>>> categories = [
...     'alt.atheism',
...     'talk.religion.misc',
...     'comp.graphics...