Correction: Fiorini, L., et al., Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data. Sensors 2017, 17, 1034

Laura Fiorini; Filippo Cavallo; Paolo Dario; Alexandra Eavis; Praminda Caleb-Solly

doi:10.3390/s19224860

,

and

¹

The BioRobotics Institute, Scuola Superiore Sant’Anna, Pontedera, 56025 Pisa, Italy

²

Alcove Limited, 44 Westbridge Road, London SW11 3PW, UK

³

Bristol Robotics Laboratory, University of West England, Bristol BS16 1QY, UK

^*

Author to whom correspondence should be addressed.

Sensors2019, 19(22), 4860;https://doi.org/10.3390/s19224860

Version Notes

Order Reprints

Abstract

A correction is presented to correct the section headings of Sections 5.1, 5.2, and 5.3 in [Sensors, 2017, 17, 1034].

The authors wish to make the following corrections to this paper []:

The section headings in Sections 5.1, 5.2, and 5.3 are the same. The correct section headings are as follows:

5.2. Cluster Analysis: Analysis of Night-Time Behavior

5.3. Analysing Similarity between Participants’ Behavior

5.4. Similarity between Participants over the Three Rooms

The authors would like to apologize for any inconvenience caused to the readers by these changes.

References

Fiorini, L.; Cavallo, F.; Dario, P.; Eavis, A.; Caleb-Solly, P. Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data. Sensors 2017, 17, 1034. [Google Scholar] [CrossRef] [PubMed]

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Correction: Fiorini, L., et al., Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data. Sensors 2017, 17, 1034

Abstract

References

Article Metrics

Citations

Article Access Statistics