Interrelation Miner

The Interrelation Miner is a method to evaluate and predict multivariate data. The method belongs to the areas of artificial intelligence and pattern recognition. The method uses the statistical analysis of the mutual relations between the variables (interrelations) and provides the class membership of the samples (e.g. positive vs. negative, sick vs. healthy, strategy 1 vs. strategy 2 vs. strategy 3) or it provides a quantitative prediction (e.g. growth, temperature).

Due to its special algorithm the Interrelation Miner Methodology is unique. In all applications up to now it proved to be better or at least as good as comparable algorithms (e.g. k-nearest neighbour or other, commercially available algorithms). The Interrelation Miner Software easily provides comparisons with available standard algorithms.

The Interrelation Miner is a highly competitive product. Confidential test calculations are easily possible (contact: info@systaim.ch).