Clustering sentences using K-means – unsupervised text classification

In this recipe, we will use the same data as in the previous chapter and use the unsupervised K-means algorithm to sort data. After you have read this recipe, you will be able to create your own unsupervised clustering model that will sort data into several classes. You can then later apply it to any text data without having to first label it.

Getting ready

We will use the packages from the previous recipes, as well as the pandas package. Install it using pip:

pip install pandas

How to do it…

In this recipe, we will preprocess the data, vectorize it, and then cluster it using K-means. Since there are usually no right answers for unsupervised modeling, evaluating the models is more difficult, but we will be able to look at some statistics, as well as the most common words in all the clusters.

Your steps are as follows:

1. Import the necessary functions and packages:

   import nltk...