TunedIT Machine Learning & Data Mining Algorithms Automated Tests, Repeatable Experiments, Meaningful Results
There are two parts to the TunedIT site:
TunedIT Research
TunedIT Research is an open platform for reproducible evaluation of machine learning and data mining algorithms. Everyone may use TunedIT tools to launch reproducible experiments and share results with others. Reproducibility is achieved through automation. Datasets and algorithms, as well as experimental results, are collected in central databases: Repository and Knowledge Base, to enable comparison of wide range of algorithms, and to facilitate dissemination of research findings and cooperation between researchers. Everyone may access the contents of TunedIT and contribute new resources and results.
TunedIT Challenge
The TunedIT project was established in 2008 as a free and open experimentation platform for data mining scientists, specialists and programmers. It was extended in 2009 with a framework for online data mining competitions, used initially for laboratory classes at universities. Today, we provide a diverse range of competition types – for didactic, scientific and business purposes.
- Student Challenge — For closed members groups. Perfectly suited to organize assignments for students attending laboratory classes. Restricted access and visibility, only for members of the group. FREE of charge
- Scientific Challenge — Open contest for non-commercial purpose. Typically associated with a conference, journal or scientific organization. Concludes with public dissemination of results and winning algorithms. May feature prizes. Fee: FREE or 20%
- Industrial Challenge — Open contest with commercial purpose. Intellectual Property can be transfered at the end. No requirement for dissemination of solutions. Fee: 30%
This looks like a possible way to generate some publicity about and interest in topic maps.
Suggestions of existing public data sets that would be of interest to a fairly broad audience?
Thinking we are likely to model some common things the same and other common things differently.
Would be interesting to compare results.