NAG Data Mining Components

More about NAG DMC

Need to know more about NAG Data Mining and Cleaning Components? Click on one of the following links or contact us to discuss your needs.

NAG’s DMC is a collection of callable components designed to help developers build fast, accurate, and robust applications for predictive analytics. You select the components you need for problem solving and readily integrate these components into your existing applications.

DMC incorporates routines for data cleaning (including imputation and outlier detection), data transformations (scaling, principal component analysis), clustering, classification, regression models and machine learning methods (neural networks, radial basis function, decision trees, nearest neighbors), and association rules. Also included are utility functions including random number generators and functions for rank ordering, sorting, mean and sum of squares updates, two-way classification comparison, and save and load models.

Who is it for?

Application developers working in areas such as life sciences, research, finance, and ISVs rely on NAG’s DMC components to enhance performance and significantly reduce development time. Data mining plays an essential part in applications in a range of business activities including:

Features & Benefits

Features

Benefits

Enhanced data cleaning functions

"Cleans" data by imputing missing values, having a detrimental effect on the quality of your analysis.

Advances in outlier identification

Identify unusual or extreme-valued data points that will have an undue influence on a fitted model.

Machine learning and pattern recognition functionality

From the intuitive analysis obtained from decision trees and nearest neighbors to nonlinear models such as radial basis functions and multi-layer perceptrons, NAG DMC includes a wide range of recent analytical developments.

Specifically designed for large data sets

Recognize the potential to create competitive advantage by unlocking the relationships in your data warehouses with multivariate statistical algorithms specifically designed for large data sets by using limited storage and out-of-core solvers.

Easy integration

Integrates into a broad range of applications including those developed in Java, C/C++, and .NET, significantly speeding up application development and easily enhancing existing or new applications.

Multiple user interfaces

Ideally suited for interfacing with other programming languages such as PERL, Java, C#, and Python. Multiple user interfaces enable quick and easy prototyping, greater control and enhanced performance. You can rely on the results and spend less time redeveloping applications.

Comprehensive documentation

DMC is supported through NAG’s thorough documentation including detailed function documents, guidance on which routines to select for particular scenarios, and example calling programs and data.

Available for your computing environments

Available for Windows, Mac OS X, Linux, Solaris, and other Unix platforms.

Standards Compliant

All functions conform fully to ANSI and to CRISP-DM (cross-industry standard process for data) allowing interoperability with other software.

Quality Assured

The validity of each component is tested on each of the machine ranges for which the product is available. Only when an implementation satisfies our stringent accuracy standards is it released. As a result, you can rely on the proven accuracy and reliability of the components to give you the right answers.