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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.

"The most important data-mining business applications, such as classification and predictive modeling, can be accomplished using just CART," says Dan Steinberg, president of Salford Systems. "Many businesses don't need to go overboard buying data-mining suites, which contain multiple data-analysis components, cost tens of thousands of dollars, and require a high level of expertise to operate. As a cost-effective stand-alone package, CART gives beginning data miners a highly accurate, easy-to-use tool that does not require technical expertise." For experienced data miners, CART is a high-performance, proven methodology that can be used as an independent data-mining system and as a companion tool that can significantly extend preprocessing capabilities, such as variable selection, for neural nets and other data-mining systems.

Accessible, Sophisticated Functionality

CART uses an intuitive, Windows-based interface that enables non-technical business users to create models quickly and interpret results easily. The software uses historical data to discover patterns, trends and relationships, and it automatically generates high-performance predictive models that can be applied to new data. This information facilitates better business decisions and increases profitability. In addition, CART can grow to fit your business by easily expanding from single-desktop applications to enterprise-wide servers accessing data marts and data warehouses.

For experienced data analysts, CART provides the following advanced features* in a combination not available in any other decision-tree package:

  • multiple automatic self-validation procedures
  • adjustable misclassification penalties
  • intelligent surrogates for missing values
  • eight choices for tree-growing criteria
  • multiple-tree, committee-of-expert methods, or bootstrap aggregation
  • a complete programming language with flow control for on-the-fly data manipulation

"CART's range of features make it an exceptional out-of-box data-analysis package for beginning and experienced data miners," says Steinberg. "Even with 'dirty' datasets, or those with many missing values, CART will develop robust, stable models. In addition, CART's default-setting performance rivals - and sometimes outperforms - neural nets."

* For more detail on CART and its advanced features, please refer to "Frequently Asked Questions and Answers About CART".

Branching Across Industries

Worldwide, CART has more than 1,000 users found in nearly all industry segments, including marketing, financial services, insurance, retail trade, health care, pharmaceutical, manufacturing, telecommunications, energy, agricultural, transportation and education. In these data-intensive industries, CART is especially efficient in discovering multi-dimensional relationships within large, complex data warehouses - the data repositories that now drive mission-critical business decisions.

"CART is an important statistical-analysis tool that we use to segment our databases and predict risk factors for the Sears Card," says Steven Li, Sears, Roebuck and Co.'s senior manager of risk technology. "The advantage of the decision-tree format is that our results are easy to interpret; especially with CART, we are able to see a great deal of detail about each of the nodes, such as the node's misclassification 'costs,' the count of data assigned to that node, and a display of the surrogate values substituted for the node."

"In addition to risk management, CART is notably successful in targeting direct mailings and improving response rates. In the financial services industry, the software is used to retain customers by making preemptive offers to mortgage holders identified as most likely to refinance their homes. In telecommunications, CART is used to identify households likely to "churn," or switch carriers in a given time frame.

CART is also used for detecting credit-card and insurance fraud; customer profiling and market segmentation; identifying cross- and up-selling opportunities; credit-card scoring; medical diagnostic-test development; predicting assembly-line failures; and myriad other business-intelligence needs.

Time-Tested, Proven Methodology

On the surface, CART's design automates several processes that traditionally require computer programming and statistical expertise. Underlying the "easy" interface, however, is a mature theoretical foundation that distinguishes CART from other methodologies and other decision trees. Salford Systems' CART is the only decision-tree system based on the original CART code developed by world-renowned Stanford University and University of California at Berkeley statisticians; this code now includes enhancements that were co-developed by Salford Systems and CART's originators.

"CART is the most accurate decision-tree software commercially available," says Steinberg. "This tree method is the fruit of a decade of machine-learning and statistical research, and our software is the only complete implementation of the original, proven algorithm."

Adaptable Across Environments

CART supports a variety of desktop stand alone and client/server operating environments. Operating systems supported include Windows 3.x, Windows 95, Windows NT, Mac OS, and UNIX. Hardware systems supported include Intel PCs, Sun, SGI, HP, Digital Alpha and VAX, and IBM RS6000 machines. CART's scalability is limited only by a system's available RAM; at the least, it requires 10 MB of disk storage. CART's data-translation engine supports data conversions for more than 70 file formats, including popular statistical-analysis packages, such as SAS® and SPSS; and spreadsheets, such as Microsoft Excel and Lotus.


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