Barros R.C., de Carvalho A.C.P.L.F., Freitas A.A. Automatic Design of Decision-Tree Induction Algorithms

Springer, 2015. — 184 p.
This book is structured in 7 chapters, as follows.
Chapter 1 Introduction.
Chapter 2 [Decision-Tree Induction]. This chapter presents the origins, basic concepts, detailed components of top-downinduction, and also other decision-tree induction strategies.
Chapter 3 [Evolutionary Algorithms and Hyper-Heuristics]. This chapter covers the origins, basic concepts, and techniques for both Evolutionary Algorithms and Hyper-Heuristics.
Chapter 4 [HEAD-DT: Automatic Design of Decision-Tree Induction Algorithms]. This chapter introduces and discusses the hyper-heuristic evolutionary algorithm that is capable of automatically designing decision-tree algorithms. Details such as the evolutionary scheme, building blocks, fitness evaluation, selection, genetic operators, and search space are covered in depth.
Chapter 5 [HEAD-DT: Experimental Analysis]. This chapter presents a thorough empirical analysis on the distinct scenarios in which HEAD-DT may be applied to. In addition, a discussion on the cost effectiveness of automatic design, as well as examples of automatically-designed algorithms and a baseline comparison between genetic and random search are also presented.
Chapter 6 [HEAD-DT: Fitness Function Analysis]. This chapter conducts an investigation of 15 distinct versions for HEAD-DT by varying its fitness function, and a new set of experiments with the best-performing strategies in balanced and imbalanced data sets is described.
Chapter 7 [Conclusions]. We finish this book by presenting the current limitations of the automatic design, as well as our view of several exciting opportunities for future work.