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Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

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): ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content