Evidential Editing K-Nearest Neighbor Classifier

A Modified Editing k-nearest Neighbor Rule

Classification of objects is an important area in a variety of fields and applications. Many different methods are available to make a decision in those cases. The knearest neighbor rule (k-NN) is a well-known nonparametric decision procedure. Classification rules based on the k-NN have already been proposed and applied in diverse substantive areas. The editing k-NN proposed by Wilson would be ...

Evolving edited k-Nearest Neighbor Classifiers

The k-nearest neighbor method is a classifier based on the evaluation of the distances to each pattern in the training set. The edited version of this method consists of the application of this classifier with a subset of the complete training set in which some of the training patterns are excluded, in order to reduce the classification error rate. In recent works, genetic algorithms have been ...

Comparing pixel-based and object-based algorithms for classifying land use of arid basins (Case study: Mokhtaran Basin, Iran)

In this research, two techniques of pixel-based and object-based image analysis were investigated and compared for providing land use map in arid basin of Mokhtaran, Birjand. Using Landsat satellite imagery in 2015, the classification of land use was performed with three object-based algorithms of supervised fuzzy-maximum likelihood, maximum likelihood, and K-nearest neighbor. Nine combinations...

Nearest neighbor classifier: Simultaneous editing and feature selection

Hilbert Space Filling Curve (hsfc) Nearest Neighbor Classifier

The Nearest Neighbor algorithm is one of the simplest and oldest classification techniques. A given collection of historic data (Training Data) of known classification is stored in memory. Then based on the stored knowledge the classification of an unknown data (Test Data) is predicted by finding the classification of the nearest neighbor. For example, if an instance from the test set is presen...