Multimodal fusion in neuroimaging combines data from multiple imaging modalities to
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …

Abstract k-Nearest neighbor (KNN) rule is a very simple and powerful classification
algorithm. In this article, we propose a new KNN-based classifier, called the local mean …

The k-nearest neighbors classifier is one of the most widely used methods of classification
due to several interesting features, such as good generalization and easy implementation …

In this work, the parallel fast condensed nearest neighbor (PFCNN) rule, a distributed
method for computing a consistent subset of a very large data set for the nearest neighbor …

In this paper, Boosting is used to determine the order in which base predictors are
aggregated into a Double-Bagging ensemble, and a subensemble is constructed by early …

Nearest neighbor classifier (NNC) is stable to the change of the training data set while
sensitive to the variation of the feature set. The combination of multiple NNCs on different …

This article describes the structure and functional content of a developed software system of
different types of data classification based on the ensemble algorithms. Also the article …

В статье предложен неоднородный ансамблевый алгоритм, предназначенный для
классификации разнотипных данных. Алгоритм основан на итерационном применении …

В статье рассматривается новый эволюционный подход к построению ансамбля
классификаторов. Предложенный подход разработан на основе генетического …

This paper proposes a method to fuse Real-valued K nearest neighbor classifier by feature
grouping. Real-valued K nearest neighbor classifier can approximate continuous-valued …