How to do it…

In the following steps, you will read in the fake news dataset, preprocess it, and then train a Random Forest classifier to detect fake news:

  1. Import pandas and read in the CSV file, fake_news_dataset.csv:
import pandas as pdcolumns = [    "text",    "language",    "thread_title",    "spam_score",    "replies_count",    "participants_count",    "likes",    "comments",    "shares",    "type",]df = pd.read_csv("fake_news_dataset.csv", usecols=columns)
  1. Preprocess the dataset by focusing on articles in English and dropping rows with missing values:
df = df[df["language"] == "english"]df = df.dropna()df = df.drop("language", axis=1
  1. Define a convenience function to convert categorical features into numerical:
features = 0feature_map = {}def add_feature(name): ...

Get Machine Learning for Cybersecurity Cookbook now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.