Spam detection is an important part of most email systems and can be useful in other areas such as text messaging. In this recipe, we will demonstrate how we can use text classification to detect spam.
We will begin with the downloading and formatting of spam and ham files. Ham refers to those emails that are not spam. Next, an OpenNLP model will be trained on the email data. We will then validate the model using an additional set of email files.