Skip to Content
Hands-On Automated Machine Learning
book

Hands-On Automated Machine Learning

by Sibanjan Das, Umit Mert Cakmak
April 2018
Beginner to intermediate content levelBeginner to intermediate
282 pages
6h 52m
English
Packt Publishing
Content preview from Hands-On Automated Machine Learning

Necessary feature transformations

As you may have noticed, features are scaled in the previous section before training machine learning algorithms. Feature transformations are usually necessary for ML algorithms to work properly. For example, as a rule of thumb, for ML algorithms that use regularization, normalization is usually applied to features.

The following is a list of use cases where you should transform your features to prepare your dataset to be ready for ML algorithms:

  • SVM expects its inputs to be in the standard range. You should normalize your variables before feeding them into the algorithm.
  • Principal Component Analysis (PCA) helps you to project your features to another space based on variance maximization. You can then select ...
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

Automated Machine Learning

Automated Machine Learning

Adnan Masood
R: Unleash Machine Learning Techniques

R: Unleash Machine Learning Techniques

Raghav Bali, Dipanjan Sarkar, Brett Lantz, Cory Lesmeister

Publisher Resources

ISBN: 9781788629898Supplemental Content