Decision Tree and Ensemble Learning Based on Ant Colony Optimization is popular PDF and ePub book, written by Jan Kozak in 2018-06-20, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Decision Tree and Ensemble Learning Based on Ant Colony Optimization can be Read Online from any device for your convenience.
Decision Tree and Ensemble Learning Based on Ant Colony Optimization Book PDF Summary
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.
Detail Book of Decision Tree and Ensemble Learning Based on Ant Colony Optimization PDF
- Author : Jan Kozak
- Release : 20 June 2018
- Publisher : Springer
- ISBN : 9783319937526
- Genre : Technology & Engineering
- Total Page : 165 pages
- Language : English
- PDF File Size : 10,9 Mb
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