Text classification

Text classification is the process of assigning predefined categories or labels to text documents. It is one of the most widely used text analysis applications, supporting tasks such as spam detection, sentiment analysis, and topic categorization.

We learned more about classification in Chapter 7, where text classification is basically a ML classification problem. From a ML perspective, text classification cannot take text as input in its raw form, so we perform text transformation, as explained in the previous section.

This section will explore preparing text for classification, training the model, and evaluating the result. We will go through the standard ML development cycle that we previously learned about.

For this example, we will use the previous review dataset to develop a sentiment analysis model. First, let’s import all the important libraries we will use and split the dataset:

import re
import numpy as np
import pandas as pd
from...