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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 this section, we'll walk through a recipe showing how to use PCA on data:

  1. Start by importing the necessary libraries and reading in the dataset:
from sklearn.decomposition import PCAimport pandas as pddata = pd.read_csv("file_pe_headers.csv", sep=",")X = data.drop(["Name", "Malware"], axis=1).to_numpy()
  1. Standardize the dataset, as is necessary before applying PCA:
from sklearn.preprocessing import StandardScalerX_standardized = StandardScaler().fit_transform(X)
  1. Instantiate a PCA instance and use it to reduce the dimensionality of our data:
pca = PCA()pca.fit_transform(X_standardized)
  1. Assess the effectiveness of your dimensionality reduction:
print(pca.explained_variance_ratio_)

The following screenshot shows the ...

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Publisher Resources

ISBN: 9781789614671Supplemental Content