Book Image

Feature Engineering Made Easy

By : Sinan Ozdemir, Divya Susarla
Book Image

Feature Engineering Made Easy

By: Sinan Ozdemir, Divya Susarla

Overview of this book

Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization.
Table of Contents (14 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface

Extending numerical features


Numerical features can undergo various methods to create extended features from them. Previously, we saw how we can transform continuous numerical data into ordinal data. Now, we will dive into extending our numerical features further. 

Before we go any deeper into these methods, we will introduce a new dataset to work with.

Activity recognition from the Single Chest-Mounted Accelerometer dataset

This dataset collects data from a wearable accelerometer, mounted on the chest, collected from fifteen participants performing seven activities. The sampling frequency of the accelerometer is 52 Hz and the accelerometer data is uncalibrated. 

The dataset is separated by participant and contains the following:

  • Sequential number
  • x acceleration
  • y acceleration
  • z acceleration
  • Label

Labels are codified by numbers and represent an activity, as follows:

  • Working at a computer 
  • Standing up, walking, and going up/down stairs 
  • Standing 
  • Walking 
  • Going up/down stairs 
  • Walking and talking with someone...