Temporal Data Mining via Unsupervised Ensemble Learning

Written By Yun Yang
Temporal Data Mining via Unsupervised Ensemble Learning
  • Publsiher : Elsevier
  • Release : 15 November 2016
  • ISBN : 0128118415
  • Pages : 172 pages
  • Rating : 4/5 from 21 reviews
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Read or download book entitled Temporal Data Mining via Unsupervised Ensemble Learning written by Yun Yang which was release on 15 November 2016, this book published by Elsevier. Available in PDF, EPUB and Kindle Format. Book excerpt: 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 via Unsupervised Ensemble Learning

Temporal Data Mining via Unsupervised Ensemble Learning
  • Author : Yun Yang
  • Publisher : Elsevier
  • Release Date : 2016-11-15
  • Total pages : 172
  • ISBN : 0128118415
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Summary : 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 ...

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  • Publisher : Springer
  • Release Date : 2018-05-20
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  • ISBN : 0128118415
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  • Publisher : Springer Nature
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Summary : Download or read online Machine Learning and Knowledge Discovery in Databases written by Frank Hutter, published by Springer Nature which was released on . Get Machine Learning and Knowledge Discovery in Databases Books now! Available in PDF, ePub and Kindle....

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Summary : The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 submissions. The papers present new ideas, original research results, and practical development ...

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  • Publisher : Unknown
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  • ISBN : 0128118415
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Summary : Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume ...

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