Data-centric Explainable Machine Learning for Land Cover Classification: A Practical Guide in R

This book introduces data-centric explainable machine learning for land cover classification. The book will introduce concepts and techniques to start data-centric explainable machine learning for land cover classification.

With this book, you will learn to:

• import satellite imagery and training sample points in R;
• prepare training data;
• perform exploratory data analysis;
• tune and train machine learning models;
• explore strategies to minimize class imbalance;
• perform explainable machine learning using the iml, DALEX, and iBreakdown packages; and
• perform data-centric explainable machine learning

“The book is easy to follow and introduces data-centric explainable machine learning to improve land cover mapping.”
– Professor Chattichai WAISURASINGHA
Associate Professor, Khon Kaen University