Using SVMs for supervised text classification

In this recipe, we will build a machine learning classifier that uses the SVM algorithm. By the end of the recipe, you will have a working classifier that you will be able to test on new inputs and evaluate using the same classification_report tools as we used in the previous sections.

Getting ready

We will continue working with the same packages that we already installed in the previous recipes.

How to do it…

We will start with the already familiar steps of dividing data into training and testing sets and creating a vectorizer. We will then train the SVM classifier and evaluate it.

Your steps are as follows:

1. Import the necessary functions and packages:

   import numpy as np
   import pandas as pd
   import string
   import pickle
   from sklearn import svm
   from sklearn import preprocessing
   from sklearn.metrics import classification_report
   from sklearn.model_selection import train_test_split
   from sklearn.feature_extraction...