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Salford Systems Introduces CART®

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.

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Salford Systems Launches MARS®, an Exclusive Predictive Modeling Solution

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.

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Leo Breiman's Election to the National Academy of Sciences

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.

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TreeNet® Most Accurate in KDDCup 2004

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.

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