Temporal Data Mining via Unsupervised Ensemble Learning.pdf

Temporal Data Mining via Unsupervised Ensemble Learning

Yun Yang

Temporal Data Mining via Unsupervised Ensemble Learning Temporal Data Mining via Unsupervised Ensemble Learning not only provides an overview of temporal data mining and an in-depth knowledge of temporal data clustering and ensemble learning techniques but also provides a rich blend of theory and practice with three proposed novel approaches. Since each temporal clustering approach favors differently structured temporal data or types of temporal data with certain assumptions, and since there is nothing universal that can solve all problems, this book enables practitioners to understand the characteristics of both clustering algorithms and the target temporal data so as to select the right approach to successfully solve each different situation. Key Features : The first novel approach is based on the ensemble of Hidden Markov Model-based partitioning clustering, associated with a hierarchical clustering refinement, to solve problems by finding the intrinsic number of clusters and model initialization problems which exist in most model-based clustering algorithms

A survey on ensemble learning | SpringerLink 30/08/2019 · Ensemble learning, as one research hot spot, aims to integrate data fusion, data modeling, and data mining into a unified framework. Specifically, ensemble learning firstly extracts a set of features with a variety of transformations. Based on these learned features, multiple learning algorithms are utilized to produce weak predictive results. Finally, ensemble learning fuses the informative

1.31 MB Taille du fichier
9780128116548 ISBN
Temporal Data Mining via Unsupervised Ensemble Learning.pdf


PC et Mac

Lisez l'eBook immédiatement après l'avoir téléchargé via "Lire maintenant" dans votre navigateur ou avec le logiciel de lecture gratuit Adobe Digital Editions.

iOS & Android

Pour tablettes et smartphones: notre application de lecture tolino gratuite

eBook Reader

Téléchargez l'eBook directement sur le lecteur dans la boutique www.ibedsma.be ou transférez-le avec le logiciel gratuit Sony READER FOR PC / Mac ou Adobe Digital Editions.


Après la synchronisation automatique, ouvrez le livre électronique sur le lecteur ou transférez-le manuellement sur votre appareil tolino à l'aide du logiciel gratuit Adobe Digital Editions.

Notes actuelles

Sofya Voigtuh

Temporal Data Mining via Unsupervised Ensemble …

Mattio Müllers

Temporal Data Mining via Unsupervised Ensemble …

Noels Schulzen

UNSUPERVISED ENSEMBLE LEARNING AND ITS APPLICATION … Philosophy and entitled: Unsupervised ensemble learning and its application to temporal data clustering. Date of Submission: 02/11/2011 Temporal data clustering can provide underpinning techniques for the discovery of intrinsic structures and can condense or summarize information contained in

Jason Leghmann

Book Description. 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 …

Jessica Kolhmann

Ensemble learning - Wikipedia In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically