Decision Tree and Ensemble Learning Based on Ant Colony Optimization

Автор: Jan Kozak

Език:

Корици: С твърди корици

Издател: Springer International Publishing AG

Наличност: Външен склад

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This book not only discusses the important topics in the area of machine learning and combinatorial...

Информация за книгата

Автор

Jan Kozak

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2018

страници

159

EAN

9783319937519

ISBN

3319937510

Enbook ID

19424271

Издател

Springer International Publishing AG

Теглоt

2605

Размери

155 x 235 x 16

Пълно описание

This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R&D.

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Decision Tree and Ensemble Learning Based on Ant Colony Optimization

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