Discipulus™ genetic-programming software is a powerful regression and classification tool.  It has significant advantages over neural-networks, classification-trees, support-vector-machines and robust-regression methods.  It is fast, powerful, and has a proven track record of results:

• Sixty to two-hundred times faster than comparable modeling techniques

• Consistently out-performs neural networks, classification trees, support vector machines and robust regression methods with less work

• Unlike neural networks, Discipulus automatically separates relevant and irrelevant inputs and easily handles highly correlated inputs

• Scaling and preprocessing of inputs is usually unnecessary
• Intelligent self-configuration means NO parameter setting
• Creates models from large data-sets quickly and easily
• Built-in protection against over-fitting
• Execution in parallel over a Windows network for enterprise level execution speed
• Easily understood models produced in C, Java or Intel Assembler for deployment

			Applications

• Prediction of corporate bankruptcy in apparently healthy firms
• Network Intrusion Detection
• Tumor Classification using microarray data
• Geological data mining for oil and gas
• Discrimination of unexploded ordnance from digital geophysical mapping at Jefferson Proving Grounds and F.E.Warren Air Force Base.
• Reverse-engineering legacy applications (see pages 12-13)
• Refinery and plant control programs
• DNA Array classification
• Financial market prediction
• Prediction of corporate financial well-being one year into the future.
• Environmental engineering