Molto spesso, nell’eseguire i test di algoritmi di clustering, è molto utile avere a disposizione degli insiemi di dati campione sintetici, ovvero creati artificialmente e che non rispecchiano dei dati reali.

A tale scopo molto utile si rivela il lavoro fatto dal Center for Data Engineering, International Institute of Information Technology, Hyderabad, INDIA

• bibtex | link
  J. R. Vennam and S. Vadapalli, "SynDECA: A Tool to Generate Synthetic Datasets for Evaluation of Clustering Algorithms," in 11th International Conference on Management of Data (COMAD 2005), Goa, India, 2005.
  @conference{syndeca2005, Address = {Goa, India},
  Author = {Jhansi Rani Vennam and Soujanya Vadapalli},
  Booktitle = {11th International Conference on Management of Data (COMAD 2005)},
  Date-Added = {2007-06-18 16:18:49 +0200},
  Date-Modified = {2007-07-03 18:34:02 +0200},
  Keywords = {clustering, tool, synthetic, dataset, generator},
  Month = {January},
  Organization = {http://cde.iiit.ac.in/syndeca},
  Title = {SynDECA: A Tool to Generate Synthetic Datasets for Evaluation of Clustering Algorithms},
  Url = {http://comad2005.persistent.co.in/COMAD2005Proc/pages027-036.pdf},
  Year = {2005},
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  Bdsk-Url-1 = {http://comad2005.persistent.co.in/COMAD2005Proc/pages027-036.pdf}
}

Lo strumento riesce a produrre dataset sintetici molto rapidamente; in genere un insieme con spazio delle feature 2D, con un milione di punti e centinaia di cluster, viene prodotto in pochi secondi.

Per ogni insieme prodotto, viene fornito dettagli sul clustering, come:

- quali punti appartengono a quali cluster
- quanti cluster
- quanti punti per cluster
- forma dei cluster
- etc.