What is AutoUniv?

AutoUniv (AU) is a tool for generating artificial data sets for the classification task, which mirror the characteristics of real data.  This achieved by designing classification models and then generating data sets from them.
AU is freely available for use by the Machine Learning and Data Mining communities in developing and testing algorithms which learn to classify.
With AU you can design models having:
  • up to 1000 attributes and ten classes
  • discrete and continous attributes
  • up to 3000 rules for a model
  • varying degrees of specialisation within rule conditions
  • attribute factorisation
  • relevant, redundant and pure noise attributes
  • varying noise levels and lift
  • rare classes
  • concept and population drift from other models
 and then generate classified examples from them in the following formats:
  • csv
  • ARFF
  • c4.5
Designed by:
Ray Hickey
AU was implemented in Win-Prolog, v4.9 from Logic Programming Associates