Service-Based Approach for Intelligent Agent Frameworks

Autor:	Mora, Randall P., Hill, Jerry L.
Rok vydání:	2011
Předmět:	Bayesian priors probabilistic grammar intelligent agent service-based framework PMML
Druh dokumentu:	Proceedings<br />Text
ISSN:	0884-5123 0074-9079
Popis:	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.
Databáze:	Networked Digital Library of Theses & Dissertations
Externí odkaz:	http://hdl.handle.net/10150/595661 Zobrazit plný text záznamu