Affordable, proven technology reveals hidden relationships; automatically generates accurate predictive models

Salford Systems, a new-generation data-mining software developer and consultant, today introduces CART®, user-friendly classification-and-regression-tree software. CART produces the most reliable classification and prediction models for applications such as profiling "best" customers, targeting direct mailings, detecting telecommunications and credit-card fraud, and managing credit risk.

Salford Systems today introduces MARS®, a high-speed flexible regression tool for data mining and predictive modeling. A natural alternative to Neural Networks and more conventional regression models, MARS was designed to solve problems such as how to predict credit card holder balances, insurance claim losses, and cell phone usage with superior forecasting accuracy. MARS builds its models automatically, self-tests to ensure validity, and graphically displays the effect of each important variable on the outcome.

Leo Breiman, one of the four creators of CART®, was elected to the National Academy of Sciences on May 1, 2001 for his seminal work in data mining, decision trees, and pattern recognition. Election to the Academy is considered one of the highest honors that can be accorded to a scientist or engineer. Leo joins CART co-author Charles J. Stone, who was elected earlier.

Salford Systems was the winner of the Teradata Center for CRM at Duke University 2003 predictive modeling and data mining tournament.

Dan Steinberg, President of Salford Systems won Japan's Nikkei Quality Control (QC) Literature Prize in 1999. The award recognizes literature that contributes to the progress and further development of quality control and quality management.

Salford Systems won an international web mining competition organized by the ACM (Association for Computing Machinery),

Jerry Friedman, Professor of Statistics, Stanford University, co-creator of CART, and creator of MARS and TreeNet was awarded the SIGKDD 2002 Innovation award for his far-reaching and profound contributions to data mining technology.

TreeNet continues to deliver consistent, world-class results, topping the field in yet another international data mining competition. In this case, one of our clients used a free three-day evaluation version of TreeNet to craft the most accurate model (classification accuracy) in the KDD Cup 2004 Physics Task. Their TreeNet submission placed second in the other four categories, resulting in a second-place overall finish.