Research On A Kind Of The Agent Pervasive Machine Learning Classifier

Pervasive Computing has developed towards machine learning, since Mark Weiser provided Pervasive Computing from 1990s to 2003 in the international Pervasive Computing conference proposed to improve the system performance using self information. This thesis presents a method of a kind of the Agent Pervasive machine learning classifier by means of the basic characteristic of pervasive computing and combing the characteristic of machine learning. For machine learning 'pervasive ability to service every field by the mobility of Agent and pervasive computing characteristic of Agent pervasive machine learning. And then, we constructe Agent pervasive computing machine learning classifier. The content is as follows:1. The basic conceptions of a kind of the pervasive computing machine learning are given;2. Analysis of the multiple classifiers fusion technology development;3. The basic conceptions and learning model of a kind of the Agent pervasive computing machine learning are given;4. The basic conceptions and learning model of a kind of the Agent pervasive computing machine learning classifier are given;5. The application of a kind of the Agent pervasive computing machine learning classifier is completed.Through the work of this paper, on one hand, we provide a new solution for machine learning in all walks of life in the universal application; on the other hand, Agent pervasive computing machine learning classifier design used in the more information composite circumstances is accomplish.