Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases

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The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.This paper proposes a suitable learning architecture for such an intelligent thermostat in the hope that it will benefit further ... (HVAC) systems in the home and office can largely be broken into two main categories: programmable and manual. ... These include offers from companies such as Nest Labs[3] and Honeywell[2].

Title:Machine Learning and Knowledge Discovery in Databases
Author: Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou
Publisher:Springer - 2015-08-28

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