This paper presents the first review of noise models in classification covering both label and
attribute noise. Their study reveals the lack of a unified nomenclature in this field. In order to …

Random forest (RF) is an ensemble learning method, and it is considered a reference due to
its excellent performance. Several improvements in RF have been published. A kind of …

Random Forest (RF) learning algorithm is considered a classifier of reference due its
excellent performance. Its success is based on the diversity of rules generated from decision …

Landsat image segmentation is important for obtaining large-scale land cover maps. The
accuracy of CNN-based Landsat image segmentation highly depends on the quantity and …

Support vector machine (SVM) algorithms have been widely used for classification in many
different areas. However, the use of a single SVM classifier is limited by the advantages and …

The correct selection of knowledge elements is the key to emergency management. Using
emergency knowledge elements, this study constructs an assertive reasoning selection …

In practical applications, Bayesian classification methods have been successfully employed.
The Naïve Bayes algorithm (NB) is a quick, successful, and well-known Bayesian …

Abstract Decision Trees (DTs) have been adapted to Multi-Label Classification (MLC).
These adaptations are known as Multi-Label Decision Trees (ML-DT). In this research, a …

Classifiers sometimes return a set of values of the class variable since there is not enough
information to point to a single class value. These classifiers are known as imprecise …

Although the standard k-nearest neighbor (KNN) algorithm has been used widely for
classification in many different fields, it suffers from various limitations that abate its …