Decision Tree and Ensemble Learning Based on Ant Colony Optimization, Kozak

Автор: Pardalos
Название: Machine Learning, Optimization, and Big Data
ISBN: 3319514687 ISBN-13(EAN): 9783319514680
Издательство: Springer
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Цена: 9224.00 р.
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Описание: This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions.

Автор: Nicosia
Название: Machine Learning, Optimization, and Big Data
ISBN: 331972925X ISBN-13(EAN): 9783319729251
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the post-conference proceedings of the Third International Workshop on Machine Learning, Optimization, and Big Data, MOD 2017, held in Volterra, Italy, in September 2017. The 50 full papers presented were carefully reviewed and selected from 126 submissions.

Автор: Cha Zhang; Yunqian Ma
Название: Ensemble Machine Learning
ISBN: 1489988173 ISBN-13(EAN): 9781489988171
Издательство: Springer
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Цена: 20896.00 р.
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Описание: The primary goal of this book is to give readers a complete treatment of the state-of-the-art ensemble learning methods. It also provides a set of applications that demonstrate the various usages of ensemble learning methods in the real-world.

Автор: Yong Shi; Yingjie Tian; Gang Kou; Yi Peng; Jianpin
Название: Optimization Based Data Mining: Theory and Applications
ISBN: 144712653X ISBN-13(EAN): 9781447126539
Издательство: Springer
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Цена: 20263.00 р.
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Описание: Optimization techniques have been widely adopted to implement various data mining algorithms. This book focuses on cutting-edge theoretical developments and real-life applications in optimization, covering a range of fields from finance to bioinformatics.

Автор: Yang Yun
Название: Temporal Data Mining via Unsupervised Ensemble Learning
ISBN: 0128116544 ISBN-13(EAN): 9780128116548
Издательство: Elsevier Science
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Цена: 7241.00 р.
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Описание: Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. . Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. . Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.

Автор: Panos Pardalos; Mario Pavone; Giovanni Maria Farin
Название: Machine Learning, Optimization, and Big Data
ISBN: 3319279254 ISBN-13(EAN): 9783319279251
Издательство: Springer
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Описание: This bookconstitutes revised selected papers from the First International Workshop onMachine Learning, Optimization, and Big Data, MOD 2015, held in Taormina, Sicily,Italy, in July 2015. The 32papers presented in this volume were carefully reviewed and selected from 73submissions.