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1
Comparison of machine learning methods to predict sleep qua..:
, In:
Proceedings of the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
,
Fritz, Hagen
;
Wu, Congyu
;
Kinney, Kerry
. - p. 222-223 , 2021
Link:
https://dl.acm.org/doi/10.1145/3486611.3492227
RT T1 <cTitle>Proceedings of the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation</cTitle>: T1 <Title>Comparison of machine learning methods to predict sleep quality from daytime activity and nightly bedroom environmental conditions</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3492227&Exemplar=1&LAN=DE A1 Fritz, Hagen A1 Wu, Congyu A1 Kinney, Kerry A1 Nagy, Zoltan PB ACM YR 2021 K1 consumer-grade sensors K1 indoor air quality K1 surveys K1 General and reference K1 Cross-computing tools and techniques K1 Empirical studies K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Classification and regression trees K1 Hardware K1 Communication hardware, interfaces and storage K1 Sensor applications and deployments K1 Estimation SP 222 OP 223 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3486611.3492227 DO https://dl.acm.org/doi/10.1145/3486611.3492227 SF ELIB - SuUB Bremen
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