Our Use Cases present the results of XTRACTIS modeling and include complete Benchmarks against Neural Networks, Boosted Trees, Random Forests, and Logistic Regression.

These studies illustrate the ability of XTRACTIS to automatically induce knowledge in the form of predictive and intelligible mathematical relationships from real-world data (public data or authorized private data).

For each application, we show how the induced décision system uses its fuzzy rules to compute explained predictions for new situations, i.e.  unknown to the learning data set.