Clustering as a major task in data mining is responsible for discovering hidden patterns in
unlabeled datasets. Finding the best clustering is also considered as one of the most …

Many factors with the perspective of bipolarity in the traditional Chinese food system “Yin
and Yang food system” manipulate with types of food simultaneously to have a balanced …

Medical data have the characteristics of particularity and complexity. Big data clustering
plays a significant role in the area of medicine. The traditional clustering algorithms are …

During the last decade, ensemble clustering has been the subject of many researches in
data mining. In ensemble clustering, several basic partitions are first generated and then a …

Intrusion Detection Systems (IDS) are designed to provide security into computer networks.
Different classification models such as Support Vector Machine (SVM) has been …

A bad partition in an ensemble will be removed by a cluster ensemble selection framework
from the final ensemble. It is the main idea in cluster ensemble selection to remove these …

Clustering ensemble is a new problem where it is aimed to extract a clustering out of a pool
of base clusterings. The pool of base clusterings is sometimes referred to as ensemble. An …

Nowadays, Canny edge detector is considered to be one of the best edge detection
approaches for the images with step form. Various overgeneralized versions of these edge …

A lot of research has been directed to the new optimizers that can find a suboptimal solution
for any optimization problem named as heuristic black-box optimizers. They can find the …

Many applications, such as image searching, image indexing, and image label
recommendations, have started using tagged images to benefit from user input. However …