ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / This paper describes a service-based Intelligent Agent (IA) approach for machine learning and data mining of distributed heterogeneous data streams. We focus on an open architecture framework that enables the programmer/analyst to build an IA suite for mining, examining and evaluating heterogeneous data for semantic representations, while iteratively building the probabilistic model in real-time to improve predictability. The Framework facilitates model development and evaluation while delivering the capability to tune machine learning algorithms and models to deliver increasingly favorable scores prior to production deployment. The IA Framework focuses on open standard interoperability, simplifying integration into existing environments.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/595661 |
| Date | 10 1900 |
| Creators | Mora, Randall P., Hill, Jerry L. |
| Contributors | Avum, Inc. |
| Publisher | International Foundation for Telemetering |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Proceedings |
| Rights | Copyright © held by the author; distribution rights International Foundation for Telemetering |
| Relation | http://www.telemetry.org/ |
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