K-nearest-neighbor query is an important query in uncertain network, which is finding the k close nodes to a specific node. We first put forward the concept of the credible nearest neighbor query in uncertain network, and give credible k-nearest-neighbor query algorithm. Credible distance is used to describe the distance between nodes in uncertain network. Fuzzy simulation is adopted to decreas...

k-Nearest Neighbor (KNN) is one of the most popular algorithms for pattern recognition. Many researchers have found that the KNN classifier may decrease the precision of classification because of the uneven density of t raining samples .In view of the defect, an improved k-nearest neighbor algorithm is presented using shared nearest neighbor similarity which can compute similarity between test ...

This paper analyzes k nearest neighbor classification with training data anonymized using anatomy. Anatomy preserves all data values, but introduces uncertainty in the mapping between identifying and sensitive values. We first study the theoretical effect of the anatomized training data on the k nearest neighbor error rate bounds, nearest neighbor convergence rate, and Bayesian error. We then v...

conclusions by comparing the results of classification using multiple classifier fusion with respect to using each classifier separately, it is found that the classifier fusion is more effective in enhancing the detection accuracy. objectives through the improvement of classification accuracy rate, this work aims to present a computer-assisted diagnosis system for malaria parasite. materials an...