Skip to Content
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 it works...

We begin by reading in our dataset and then standardizing it, as in the recipe on standardizing data (steps 1 and 2). (It is necessary to work with standardized data before applying PCA). We now instantiate a new PCA transformer instance, and use it to both learn the transformation (fit) and also apply the transform to the dataset, using fit_transform (step 3). In step 4, we analyze our transformation. In particular, note that the elements of pca.explained_variance_ratio_ indicate how much of the variance is accounted for in each direction. The sum is 1, indicating that all the variance is accounted for if we consider the full space in which the data lives. However, just by taking the first few directions, we can account for ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Hands-On Machine Learning for Cybersecurity

Hands-On Machine Learning for Cybersecurity

Soma Halder, Sinan Ozdemir
Machine Learning on Kubernetes

Machine Learning on Kubernetes

Faisal Masood, Ross Brigoli

Publisher Resources

ISBN: 9781789614671Supplemental Content