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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| tomato_cluster_analysis_results.zip | 2018-09-23 | 1.8 MB | |
| tomato_data_v01.zip | 2018-09-22 | 174.8 kB | |
| clustermatch-v0.1.2.zip | 2018-09-15 | 728.2 kB | |
| README.md | 2018-05-20 | 1.0 kB | |
| Totals: 4 Items | 2.7 MB | 0 | |
clustermatch
Title: Clustermatch: discovering hidden relations in highly-diverse kinds of qualitative and quantitative data without standardization
Authors: Milton Pividori, Andres Cernadas, Luis de Haro, Fernando Carrari, Georgina Stegmayer and Diego H. Milone
sinc(i) (Research institute for signals, systems and computational intelligence) - http://sinc.unl.edu.ar
* Corresponding author: mpividori@sinc.unl.edu.ar
Description
Clustermatch is an efficient clustering method for processing highly diverse data. It can handle very different data types (such as numerical and categorical), in the presence of linear or non-linear relationships, also with noise, and without the need of any previous pre-processing. The article describing the method has been sent for publication.
If you want to quickly test Clustermatch, you can access an online web-demo from here.
For the most up-to-date installation and usage instructions go to: https://bitbucket.org/sinc-lab/clustermatch