Decision tree and ensemble learning based on ant colony optimization / Jan Kozak
نوع المادة : نصاللغة: الإنجليزية السلاسل:Studies in computational intelligence ; 781.الناشر:Cham : Springer, 2019وصف:xi, 159 pages : illustrationsنوع المحتوى:- text
- unmediated
- volume
- 9783030067168
- 3319937529
- 9783319937526
- 9783319937533
- QA402.5 .K693 2019
نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
---|---|---|---|---|---|---|---|
كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA402.5 .K693 2019 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30020000208136 |
Browsing UAE Federation Library | مكتبة اتحاد الإمارات shelves, Shelving location: General Collection | المجموعات العامة إغلاق مستعرض الرف(يخفي مستعرض الرف)
QA402.5 .A38 2001 Advances in mathematical programming and financial planning / | QA402.5 D64 2004 Ant colony optimization / | QA402.5 D64 2004 Ant colony optimization / | QA402.5 .K693 2019 Decision tree and ensemble learning based on ant colony optimization / | QA402.5 .M4148 2012 Metaheuristics in water, geotechnical and transport engineering / | QA402.5 .M4148 2012 Metaheuristics in water, geotechnical and transport engineering / | QA402.5 .M58 1998 An introduction to genetic algorithms / |
Includes bibliographical references
Theoretical Framework -- Evolutionary Computing Techniques in Data Mining -- Ant Colony Decision Tree Approach -- Adaptive Goal Function of the ACDT Algorithm -- Examples of Practical Application
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