QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting r...

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Bibliographic Details
Main Authors: Ardjan Zwartjes, Paul J. M. Havinga, Gerard J. M. Smit, Johann L. Hurink
Format: Article
Language:English
Published: MDPI AG 2016-10-01
Series:Sensors
Subjects:
wireless sensor networks
unsupervised learning
classification algorithms
Naive Bayes
semi-supervised learning
adaptive
Online Access:http://www.mdpi.com/1424-8220/16/10/1629

Internet

http://www.mdpi.com/1424-8220/16/10/1629

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