software . 2020

Supplementary Materials for 'New Cluster Selection and Fine-grained Search for k-Means Clustering and Wi-Fi Fingerprinting'

Joaquín Torres-Sospedra; Darwin Quezada-Gaibor; Germán Mendoza-Silva; Jari Nurmi; Yevgeny Koucheryavy; Joaquín Huerta;
Open Source
  • Published: 04 Jun 2020
  • Publisher: Zenodo
Abstract
This package includes the function localclustering_kmeans.m which was originally included in Octave 5.1.0 Statistical Package as kmeans.m. It was developed by Soren Hauberg (2011), Daniel Ward (2012) and Lachlan Andrew (2015-2016); and released under GNU General Public License. The authors gratefully acknowledge funding from Ministerio de Ciencia, Innovación y Universidades (INSIGNIA, PTQ2018-009981); European Union's H2020 Research and Innovation programme under the Marie Skłodowska-Curie grant agreement No.813278 (A-WEAR, http://www.a-wear.eu/); and Universitat Jaume I (PREDOC/2016/55).}
Subjects
free text keywords: Indoor Positioning, Clustering, k-NN, k-Means
Funded by
EC| A-WEAR
Project
A-WEAR
A network for dynamic WEarable Applications with pRivacy constraints
  • Funder: European Commission (EC)
  • Project Code: 813278
  • Funding stream: H2020 | MSCA-ITN-EJD
Validated by funder
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Zenodo
Software . 2020
Provider: Datacite
Zenodo
Software . 2020
Provider: Datacite
Zenodo
Software . 2020
Provider: Datacite
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