Download aΒ sample projectΒ for Viscovery SOMine 8.1 along with its corresponding data. (Also available for version 8.0.)
The project demonstrates object classification. The goal of the application is to identify 26 capital letters from 16 pre-processed attributes extracted from optical image data of the letters (such as raster scan images).
We gratefully acknowledge the UCI Machine Learning Repository as the source for the data used in this example project:
Lichman, M. (2013). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science.
View online demos of Viscovery software and applications.