This paper presents a new approach to identifying and eliminating mislabeled training instances for supervised learning. The goal of this approach is to improve classiication accuracies produced by learning algorithms by improving the quality of the training data. Our approach uses a set of learning algorithms to create classiiers that serve as noise lters for the training data. We evaluate sin...

CONTEXT Choosing to pursue an advanced degree in athletic training appears to indicate professional commitment and passion for the profession. Currently, there is a paucity of information regarding why some athletic trainers pursue enrollment in a postprofessional athletic training program (PPATP), indicating commitment to the profession, but later depart for another primary role outside of ath...

The interconnected networks have many policies and traffic environments. The inconsistency between networks results in set of conflictions that debase the entire performance. The convergence process takes sometime to adapt the sub-networks, this lags the service time at all levels. The inconsistency between the sub-networks during this paper concerns on ten elements: Packet Length (PL) and form...

Neural networks are still very important part of artificial intelligence. RBF networks seems to be more powerfull than that based on sigmoid function. Error Correction is second order training algorithm dedicated for RBF networks. The paper proposes method for improvement this algorithm by elimination of inconsistent patterns. The approach is also experimentally confirmed.

In previous work we advocated continued development of specifications in the presence of inconsistency. To support this we presented quasi-classical (QC) logic for reasoning with inconsistent specifications. The logic allows the derivation of non-trivial classical inferences from inconsistent information. In this paper we present a development called labelled QC logic, and some associated analy...

In this paper we present a framework of reasoning with inconsistent ontologies, in which pre-defined selection functions are used to deal with concept relevance. We examine how the notion of ”concept relevance” can be used for reasoning with inconsistent ontologies. We have implemented a prototype called PION (Processing Inconsistent ONtologies), which is based on a syntactic relevance-based se...

There has always been interest in inconsistency in science, not least within science itself as scientists strive to devise a consistent picture of the universe. Some important early landmarks in this history are Copernicus’s criticism of the Ptolemaic picture of the heavens, Galileo’s claim that Aristotle’s theory of motion was inconsistent, and Berkeley’s claim that the early calculus was inco...

Context & motivation. During model-based engineering, numerous diagrams are created , some of which document the same behavioral properties of the system from different perspectives (cf. [1]). In industrial practice these diagrams are often developed or revised independently of each other. In consequence, inconsistencies will almost inevitably arise during the development. This situation may, f...