Parallel Computing TEDA Clustering Algorithm

Versione 1.0.1 (15,2 KB) da X.Gu&P.Angelov
The source code of the parallel computing TEDA clustering algorithm
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Aggiornato 11 nov 2018

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The package contains:

1. ParallelTEDAClustering.m - The source code of the parallel computing TEDA clustering algorithm;

2. demo.m - The demo

Reference:
Gu X., Angelov P.P., Gutierrez G., Iglesias J.A., Sanchis A. (2017) Parallel Computing TEDA for High Frequency Streaming Data Clustering. In: Angelov P., Manolopoulos Y., Iliadis L., Roy A., Vellasco M. (eds) Advances in Big Data. INNS 2016. Advances in Intelligent Systems and Computing, vol 529. Springer, Cham

Please cite this algorithm using the above reference if this code helps.

For any queries about the codes, please contact Prof. Plamen P. Angelov (p.angelov@lancaster.ac.uk) and Dr. Xiaowei Gu (x.gu3@lancaster.ac.uk)

Programmed by Xiaowei Gu

Cita come

Gu X., Angelov P.P., Gutierrez G., Iglesias J.A., Sanchis A. (2017) Parallel Computing TEDA for High Frequency Streaming Data Clustering. In: Angelov P., Manolopoulos Y., Iliadis L., Roy A., Vellasco M. (eds) Advances in Big Data. INNS 2016. Advances in Intelligent Systems and Computing, vol 529. Springer, Cham

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Creato con R2018a
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Versione Pubblicato Note della release
1.0.1

Updated the reference
1.0.0