Statistics

Generalized mean

Computer science

k-nearest neighbors algorithm

Pattern recognition (psychology)

Mathematics

Categorical variable

Outlier

Nearest neighbor search

Parametric statistics

Artificial intelligence

Classifier (UML)

Expert Systems with Applications

K-nearest neighbor (KNN) rule is a well-known non-parametric classifier that is widely used in pattern recognition. However, the sensitivity of the neighborhood size k always seriously degrades the KNN-based classification performance, especially in the case of the small sample size with the existing outliers. To overcome this issue, in this article we propose a generalized mean distance-based k-nearest neighbor classifier (GMDKNN) by introducing multi-generalized mean distances and the nested generalized mean distance that are based on the characteristic of the generalized mean. In the proposed method, multi-local mean vectors of the given query sample in each class are calculated by adopting its class-specific k nearest neighbors. Using the achieved k local mean vectors per class, the corresponding k generalized mean distances are calculated and then used to design the categorical nested generalized mean distance. In the classification phase, the categorical nested generalized mean distance is used as the c...

A generalized mean distance-based k-nearest neighbor classifier