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Journal ArticleDOI

A K-Means Clustering Algorithm

J. A. Hartigan, +1 more
- 01 Mar 1979 - 
- Vol. 28, Iss: 1, pp 100-108
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This article is published in Journal of The Royal Statistical Society Series C-applied Statistics.The article was published on 1979-03-01. It has received 10702 citations till now. The article focuses on the topics: Canopy clustering algorithm & Correlation clustering.

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Electrocardiogram analysis using a combination of statistical, geometric, and nonlinear heart rate variability features

TL;DR: Analysis shows that the proposed combination of 11 linear and nonlinear HRV features gives high classification accuracy when nonlinear features are extracted for five periods, and RF algorithm proved to be highly efficient and accurate in both binary and multiclass classification of HRV records.
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Cluster Analysis of Rural, Urban, and Curbside Atmospheric Particle Size Data

TL;DR: In this article, continuous multivariate particle size data have been collected using aerosol particle size spectrometers sited at four locations within the UK: Harwell (Oxfordshire), Regents Park ( London); British Telecom Tower (London); and Marylebone Road (London).
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Positive Impact of Mindfulness Meditation on Mental Health of Female Teachers during the COVID-19 Outbreak in Italy.

TL;DR: It is concluded that mindfulness-based training can effectively mitigate the psychological negative consequences of the Covid-19 outbreak, helping in particular to restore well-being in the most vulnerable individuals.
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Visualizing association rules in hierarchical groups

TL;DR: A new interactive visualization method, the grouped matrix representation, which allows to intuitively explore and interpret highly complex scenarios and can be used to analyze large sets of association rules using the R software for statistical computing.
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A New Approach to Model Load Levels in Electric Power Systems With High Renewable Penetration

TL;DR: In this article, the concept of system states is introduced to better incorporate chronological information in power system models, thereby resulting in a more accurate representation of system outcomes such as electricity prices and total cost.
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