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. 2019 Nov 7;19(22):4860. doi: 10.3390/s19224860

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

Laura Fiorini 1,*, Filippo Cavallo 1, Paolo Dario 1, Alexandra Eavis 2, Praminda Caleb-Solly 3
PMCID: PMC6891646  PMID: 31703476

Abstract

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

Keywords: behavioural models, unsupervised machine learning, cognitive health assessment, real-home settings


The authors wish to make the following corrections to this paper [1]:

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

  • 1.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. doi: 10.3390/s17051034. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Sensors (Basel, Switzerland) are provided here courtesy of Multidisciplinary Digital Publishing Institute (MDPI)

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