3. Developing a Text classifier

Activity 5: Developing End-to-End Text Classifiers

Solution

Let's build an end-to-end classifier that helps classify Wikipedia comments. Follow these steps to implement this activity:

1. Open a Jupyter notebook.
2. Insert a new cell and add the following code to import the necessary packages:

   import pandas as pd
   import seaborn as sns
   import matplotlib.pyplot as plt
   %matplotlib inline
   import re
   import string
   from nltk import word_tokenize
   from nltk.corpus import stopwords
   from nltk.stem import WordNetLemmatizer
   from sklearn.feature_extraction.text import TfidfVectorizer
   from sklearn.model_selection import train_test_split
   from pylab import *
   import nltk
   import warnings
   warnings.filterwarnings('ignore')
   from sklearn.metrics import accuracy_score,roc_curve,classification_report,confusion_matrix,precision_recall_curve,auc

3. In this step, we will read a data file. It has two columns: comment_text and toxic. The comment_text column...