For Immediate Release
September 1, 2004

NAG DMC 2.0 - Data Mining and Cleaning Components ---
Next Generation Data Mining Algorithms Now Available

(Downers Grove, IL) A wide range of business, government, and academic
research initiatives that had previously been limited by the
effectiveness of commercially available data mining software can now
build practical and highly functional data mining applications using the
newly released version 2.0 of NAG Data Mining and Cleaning Components
(DMC 2.0). DMC 2.0 is the first commercially available data mining
application development toolkit that uses results from a three-year
European Union funded project, EUREDIT, among other advances in data
mining techniques developed by the Numerical Algorithms Group, a global
collaborative network of 300+ computer scientists and mathematical
experts that work together to solve complex mathematical problems.

DMC 2.0 improvements over previous commercially available data mining
applications include:

1) enhanced DATA CLEANING to resolve the problems of missing,
invalid or incomplete data (data imputation methods);

2) advances in OUTLIER IDENTIFICATION to determine which datasets
are suitable for analysis;

3) newly MEMORY-EFFICIENT MULTIVARIATE STATISTICAL METHODS that have
been the traditional core of data mining techniques; and,

4) a wide range of added functionality for MACHINE LEARNING and
PATTERN RECOGNITION.

(For a complete list of DMC 2.0 functionality please see
http://www.nag.com/numeric/DR/Drfunctionality.asp .)
The European Union funded EUREDIT project in which many of the DMC 2.0
methods were first developed was geared to find new statistical methods
important to various areas of government-sponsored socioeconomic
studies. Mathematical experts associated with NAG further developed
these algorithms and combined them with other computational functions
for the breadth of data mining functionality including data cleaning,
data transformations, outlier detection, clustering, classification,
regression, association rules, and components for utility functions.

A hyperlinked PDF User Guide directs users to detailed function
documents for the problem they wish to solve. Written in ANSI C with
simple function interfaces, NAG DMC 2.0 is ideally suited for
interfacing with other programming languages such as PERL, Java, C#, and
Python. NAG DMC 2.0 is currently available for Windows. Mac OS X,
Linux, AIX (32-bit), Solaris, Alpha versions will be available later
this month.

Unlike most other commercially available data mining tools, DMC 2.0,
like earlier releases of NAG Data Mining Components, is designed to be
incorporated into the user=92s application rather than requiring the user
to learn a new interface to gain access to additional techniques. Users
select the components they need for problem solving and can readily
integrate these components into existing applications.

NAG (www.nag.com) is a 30-year-old company dedicated to making
cross-platform mathematical, statistical, data mining components and
tools for developers as well as 3D visualization application development
environments. It operates worldwide with hubs in Chicago (Downers
Grove), UK (Oxford), and Tokyo. Today it serves over 10,000 sites
worldwide in finance, engineering, and scientific research as well as
commercial software firms such as PeopleSoft, IBM/Informix, Intel, and
many others.