Data preparation is the foundation of any successful machine learning project. This volume provides a comprehensive guide to cleaning, transforming, and splitting data for machine learning using R, including handling missing values, feature scaling, and stratified sampling. Practical examples and R code demonstrate how to optimize datasets for predictive modeling. The volume is essential for data scientists and machine learning practitioners seeking to build robust models.

eBook - PDF
Statistics with R for Machine Learning: Volume 1 Data Preparation and Splitting with R for Machine Learning
- 298 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Statistics with R for Machine Learning: Volume 1 Data Preparation and Splitting with R for Machine Learning
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Edition
0Table of contents
- Cover
- Title Page
- Copyright
- ABOUT THE AUTHOR
- TABLE OF CONTENTS
- List of Tables
- Preface
- Chapter 1 Introduction
- Chapter 2 Clean the Raw Data
- Chapter 3 Splitting Data
- Bibliography
- Index
- Back Cover