Temporal Data Mining via Unsupervised Ensemble Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Temporal Data Mining via Unsupervised Ensemble Learning write by Yun Yang. This book was released on 2016-11-15. Temporal Data Mining via Unsupervised Ensemble Learning available in PDF, EPUB and Kindle. 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. Includes fundamental concepts and knowledge, covering all key tasks and techniques of temporal data mining, i.e., temporal data representations, similarity measure, and mining tasks Concentrates on temporal data clustering tasks from different perspectives, including major algorithms from clustering algorithms and ensemble learning approaches Presents a rich blend of theory and practice, addressing seminal research ideas and looking at the technology from a practical point-of-view
Temporal Data Mining
Temporal Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Temporal Data Mining write by Theophano Mitsa. This book was released on 2010-03-10. Temporal Data Mining available in PDF, EPUB and Kindle. From basic data mining concepts to state-of-the-art advances, this book covers the theory of the subject as well as its application in a variety of fields. It discusses the incorporation of temporality in databases as well as temporal data representation, similarity computation, data classification, clustering, pattern discovery, and prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web usage mining, and spatiotemporal data mining. Along with various state-of-the-art algorithms, each chapter includes detailed references and short descriptions of relevant algorithms and techniques described in other references.
Unsupervised Ensemble Learning and Its Application to Temporal Data Clustering
Unsupervised Ensemble Learning and Its Application to Temporal Data Clustering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Unsupervised Ensemble Learning and Its Application to Temporal Data Clustering write by Yun Yang. This book was released on 2011. Unsupervised Ensemble Learning and Its Application to Temporal Data Clustering available in PDF, EPUB and Kindle.
Recent Advances in Internet of Things and Machine Learning
Recent Advances in Internet of Things and Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recent Advances in Internet of Things and Machine Learning write by Valentina E. Balas. This book was released on 2022-02-14. Recent Advances in Internet of Things and Machine Learning available in PDF, EPUB and Kindle. This book covers a domain that is significantly impacted by the growth of soft computing. Internet of Things (IoT)-related applications are gaining much attention with more and more devices which are getting connected, and they become the potential components of some smart applications. Thus, a global enthusiasm has sparked over various domains such as health, agriculture, energy, security, and retail. So, in this book, the main objective is to capture this multifaceted nature of IoT and machine learning in one single place. According to the contribution of each chapter, the book also provides a future direction for IoT and machine learning research. The objectives of this book are to identify different issues, suggest feasible solutions to those identified issues, and enable researchers and practitioners from both academia and industry to interact with each other regarding emerging technologies related to IoT and machine learning. In this book, we look for novel chapters that recommend new methodologies, recent advancement, system architectures, and other solutions to prevail over the limitations of IoT and machine learning.
Intelligent Systems
Intelligent Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Intelligent Systems write by André Britto. This book was released on 2021-11-27. Intelligent Systems available in PDF, EPUB and Kindle. The two-volume set LNAI 13073 and 13074 constitutes the proceedings of the 10th Brazilian Conference on Intelligent Systems, BRACIS 2021, held in São Paolo, Brazil, in November-December 2021. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 192 submissions.The contributions are organized in the following topical sections: Part I: Agent and Multi-Agent Systems, Planning and Reinforcement Learning; Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization, Knowledge Representation, Logic and Fuzzy Systems; Machine Learning and Data Mining. Part II: Multidisciplinary Artificial and Computational Intelligence and Applications; Neural Networks, Deep Learning and Computer Vision; Text Mining and Natural Language Processing. Due to the COVID-2019 pandemic, BRACIS 2021 was held as a virtual event.
