Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Feature Engineering Cookbook

You're reading from   Python Feature Engineering Cookbook Over 70 recipes for creating, engineering, and transforming features to build machine learning models

Arrow left icon
Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781789806311
Length 372 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Soledad Galli Soledad Galli
Author Profile Icon Soledad Galli
Soledad Galli
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Foreseeing Variable Problems When Building ML Models 2. Imputing Missing Data FREE CHAPTER 3. Encoding Categorical Variables 4. Transforming Numerical Variables 5. Performing Variable Discretization 6. Working with Outliers 7. Deriving Features from Dates and Time Variables 8. Performing Feature Scaling 9. Applying Mathematical Computations to Features 10. Creating Features with Transactional and Time Series Data 11. Extracting Features from Text Variables 12. Other Books You May Enjoy

Applying Mathematical Computations to Features

New features can be created by combining two or more variables. Variables can be combined automatically or by using domain knowledge of the data and the industry. For example, in finance, we combine information about the income and the acquired debt to determine the disposable income:

disposable income = income - total debt.

Similarly, if a client has debt across many financial products, for example, a car loan, a mortgage, and credit cards, we can determine the total debt by adding all of those variables up:

Total debt = car loan balance + credit card balance + mortgage balance

In the previous examples, the mathematical functions used to combine the existing variables are derived via domain knowledge of the industry. We can also combine variables automatically, by creating polynomial combinations of the existing variables in the...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at £16.99/month. Cancel anytime