Charles River Analytics today announced the launch of its new Bayesian belief network modeling tool, BNet.EngineKit 1.0. BNet.EngineKit is a developer toolkit for researchers and
engineers to use to embed belief networks in software applications. Unique in its focus on clear APIs with the right functionality, BNet.EngineKit offers software developers who are not
inference algorithm specialists a chance to use Bayesian networks without spending years learning about them.
Zach Cox, software engineer and chief developer of BNet.EngineKit and BNet.Builder, notes, "EngineKit 1.0 includes learning functionality that allows you to learn your CPTs from data. Two
easy-to-use algorithms learn CPTs when you have data for all nodes in your network (fully observed) and when you have missing data or hidden nodes (partially observed). The learning
algorithms use a standard interface for obtaining data, so you can also create your own implementation and provide data from any custom source."
BNet.EngineKit is part of Charles River Analytics' family of Bayesian Network products, including BNet.Builder. To read about upcoming product releases and user tips, you can sign up for
the BNet newsletter at http://www.cra.com/commercial-products-services/bnet-news.asp.
BNet.EngineKit is available directly from Charles River Analytics. For additional information or a free trial version:
* Contact Zach Cox at 705 721 8395 or e-mail e-mail protected from spam bots
* Or visit: http://www.cra.com/bnet
About Charles River Analytics: Since 1983, Charles River Analytics has been delivering intelligent systems that turn our clients' data into information they can use to make decisions. The
company has shown stable, steady growth and profitability for over two decades. Its research and development work for the US federal government has resulted in a series of successful
commercial products. In the coming years, the company looks forward to continued growth in its core R&D contracting business and in new product ventures.