An Algorithm for Optimizing Multidimensional K-NN Queries in Wireless Sensor Networks;

Based on the principle of blind steganalysis that separate stego-images from original images by classifier with image features vectors,this paper proposes a method of performing feature selection with classifiers based on K-NN and SVM.

In k-NN method same factor is assigned to each attribute when computing the dissimilarity of two different training samples,as a result,the accuracy of classification gets worse and even confusion will come into being especially when there are many irrelevant attributes.

This dissertation mainly presents two new classification methods:the k-NN classification method based on a evidence reasoning model and the k-NN classification method based on variable precision rough set model.