Classification using distance nearest neighbours

Smoothing Using Nearest Neighbours

Nearest Neighbours Search Using the PM-Tree

We introduce a method of searching the k nearest neighbours (k-NN) using PM-tree. The PM-tree is a metric access method for similarity search in large multimedia databases. As an extension of M-tree, the structure of PM-tree exploits local dynamic pivots (like M-tree does it) as well as global static pivots (used by LAESA-like methods). While in M-tree a metric region is represented by a hyper-...

Nearest Neighbour Distance Matrix Classification

A distance based classification is one of the popular methods for classifying instances using a point-to-point distance based on the nearest neighbour or k-NEAREST NEIGHBOUR (k-NN). The representation of distance measure can be one of the various measures available (e.g. Euclidean distance, Manhattan distance, Mahalanobis distance or other specific distance measures). In this paper, we propose ...

Nearest Neighbours without k: A Classification Formalism Based on Probability

Feature Reduction and Nearest Neighbours

Feature reduction is a major preprocessing step in the analysis of highdimensional data, particularly from biomolecular high-throughput technologies. Reduction techniques are expected to preserve the relevant characteristics of the data, such as neighbourhood relations. We investigate the neighbourhood preservation properties of feature reduction empirically and theoretically. Our results indic...