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From the Publisher… an enjoyable read and offers new insights into a computational paradigm that helps to bridge the gap between applications of GP and ML, as well as substantial source code and GUI systems supporting this topic. … The best feature of this book is its simple presentation style, which includes both mathematics and visual graphics for the uninitiated. For these reasons, it is likely that the book will become an essential source of reference for students, practitioners and young researchers alike.
— Minds & Machines, 2012
... provides readers with tools and insights to apply genetic programming (GP) to classical machine learning problems. … The most important aspect of this book is the accompanying code/software. Examples in the book are derived from these tools. This enables the reader to actively learn the material by practicing on the examples. … A graduate student interested in machine learning would find this book very useful. The accompanying software can be downloaded and the student can practice and understand a variety of machine learning problems. …It also serves well machine learning researchers who are interested in how genetic programming can be used for their problems. Hopefully, this will lead to application of GP to new machine learning problems such as reinforcement learning and active learning. ... a good practitioners guide for system designers employing machine learning to solve industrial problems.
— K. Veeramachaneni, Massachusetts Institute of Technology, in Genetic Programming and Evolvable Machines (2011), 12:179-180