Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

DeepDyve requires Javascript to function. Please enable Javascript on your browser to continue.

Automatic Design of Decision-Tree Induction Algorithms

Part of the SpringerBriefs in Computer Science Book Series

DOI: 10.1007/978-3-319-14231-9

ISBN: 978-3-319-14230-2

Publisher: Springer International Publishing - Springer Journals

Feb 5, 2015

Available

Introduction

Barros, Rodrigo C.; de Carvalho, André C. P. L. F.; Freitas, Alex A.

Pages: 1 –5

[Classification, which is the data mining task of assigning objects to predefined categories, is widely used in the process of intelligent decision making.]
Available

Decision-Tree Induction

Barros, Rodrigo C.; de Carvalho, André C. P. L. F.; Freitas, Alex A.

Pages: 7 –45

[Decision-tree induction algorithms are highly used in a variety of domains for knowledge discovery and pattern recognition. They have the advantage of producing a comprehensible classification/regression model and satisfactory accuracy levels in several application domains, such as medical...
Available

Evolutionary Algorithms and Hyper-Heuristics

Barros, Rodrigo C.; de Carvalho, André C. P. L. F.; Freitas, Alex A.

Pages: 47 –58

[This chapter presents the basic concepts of evolutionary algorithms (EAs) and hyper-heuristics (HHs), which are computational techniques directly explored in this book. EAs are well-known population-based metaheuristics. They have been employed in artificial intelligence over several years with...
Available

HEAD-DT: Automatic Design of Decision-Tree Algorithms

Barros, Rodrigo C.; de Carvalho, André C. P. L. F.; Freitas, Alex A.

Pages: 59 –76

[As presented in Chap. 2, for the past 40 years researchers have attempted to improve decision-tree induction algorithms, either by proposing new splitting criteria for internal nodes, by investigating pruning strategies for avoiding overfitting, by testing new approaches for dealing with missing...
Available

HEAD-DT: Experimental Analysis

Barros, Rodrigo C.; de Carvalho, André C. P. L. F.; Freitas, Alex A.

Pages: 77 –139

[In this chapter, we present several empirical analyses that assess the performance of HEAD-DT in different scenarios. We divide these analyses into two sets of experiments, according to the meta-training strategy employed for automatically designing the decision-tree algorithms. As mentioned in...
Available

HEAD-DT: Fitness Function Analysis

Barros, Rodrigo C.; de Carvalho, André C. P. L. F.; Freitas, Alex A.

Pages: 141 –170

[In Chap. 4, more specifically in Sect. 4.4, we saw that the definition of a fitness function for the scenario in which HEAD-DT evolves a decision-tree algorithm from multiple data sets is an interesting and relevant problem. In the experiments presented in Chap. 5, Sect. 5.2, we employed a...
Available

Conclusions

Barros, Rodrigo C.; de Carvalho, André C. P. L. F.; Freitas, Alex A.

Pages: 171 –176

[We presented in this book an approach for the automatic design of decision-tree induction algorithms, namely HEAD-DT (Hyper-Heuristic Evolutionary Algorithm for Automatically Designing Decision-Tree Induction Algorithms).]

results per page

Prev
1
Next

Browse All eBooks