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Product details:
- ISBN 10: 3319937529
- ISBN 13: 9783319937526
- Author: Jan Kozak
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.
Table of contents:
1. Theoretical Framework
Part I. Adaptation of Ant Colony Optimization to Decision Trees
2. Evolutionary Computing Techniques in Data Mining
3. Ant Colony Decision Tree Approach
4. Adaptive Goal Function of the ACDT Algorithm
5. Examples of Practical Application
Part II. Adaptation of Ant Colony Optimization to Ensemble Methods
6. Ensemble Methods
7. Ant Colony Decision Forest Approach
8. Adaptive Ant Colony Decision Forest Approach
9. Summary
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