In instance-based classifiers, there is a need for storing a large number of samples as
training set. In this work, we propose an instance reduction method based on hyperrectangle …

Nearest neighbor (NN) rule is one of the simplest and the most important methods in pattern
recognition. In this paper, we propose a kernel difference-weighted k-nearest neighbor (KDF …

Magnetic resonance imaging exhibits high sensitivity but low specificity for breast cancer.
The present study aimed to investigate whether combining morphology, texture features and …

In instance-based learning, a training set is given to a classifier for classifying new
instances. In practice, not all information in the training set is useful for classifiers. Therefore …

Nowadays, automatic defects detection in MR images is very important in many diagnostic
and therapeutic applications. Because of high quantity data in MR images and blurred …

Due to the large data size of 3D MR brain images and the blurry boundary of the
pathological tissues, tumor segmentation work is difficult. This paper introduces a …

This paper presents a new classification method utilizing distance-based decision surface
with nearest neighbor projection approach, called DDC. Kernel type of DDC has been …

In instance-based classifiers, there is a need for storing a large number of samples as a
training set. In this paper, we propose a large symmetric margin instance selection …

For many real world problems we must perform classification under widely varying amounts
of computational resources. For example, if asked to classify an instance taken from a bursty …

Résumé La méthode des K-plus proches voisins K-ppv (Ang. K-Nearest Neighbors K-NN)
est une méthode de classification supervisée; elle est basée sur le calcul de la similarité …