for creating understandable
computational models
What it is
A universal tool for creating understandable computational models from data.
It combines fuzzy logic based machine learning methods. Fully implemented in C++, mlf is integrated into Mathematica.
Its differential advantage
It creates understandable, numerically optimized computational models.
Fuzzy logic based approaches create linguistic interpretable models, which can be computed like black boxes.
Mathematica's unique computing and programming environment allows quickest customization and configuration of solution integration.
Download mlf white paper.
New in Version 1.6
- Mathematica 6 support (compatible with Mathematica 5.2).
- Reporter: Run comprehensive modelling tasks and compare results.
- PartialDependencyPlot: graphically compare one or two input variables with the goal variable.
Download a detailed description of the
new features of version 1.6.
For whom it is
professionals, who want to extract models from data:
- business and financial engineers
- process- and manufacturing engineers
- quality assurance professionals
Experts, who want to integrate data mining and machine learning solutions
- knowledge engineers
- machine learning experts
Its coverage
- Analysis
- Prediction
- Visualization Information
Get further information from:
mlf@unisoftwareplus.com