A classifier capable of rule refinement

Abstract

In ubiquitous environment, too much information is generated from a lot of sensors, and people want to obtain the appropriately classified information from the information. Decision tree algorithm like C4.5 is much useful in the field of data mining or machine learning system. Because this is fast and deduces good result on the problem of classification. This paper proposes three methods using decision tree for solving a classification problem. First, this paper suggest about the extended data expression. Second, a classifier, UChoo, based on the extended data expression is described. Third, this paper is to describe about rule generation. The rules expressed in the newly suggested method have almost the same information contents as compared with the original data set. The information is gotten from the sensors becomes large amount of data as the ubiquitous computation environment develops, therefore it is impossible to keep all information in memory. However, using suggested method, this problem is solved smoothly without losing almost the information.