Among the data clustering algorithms, the k-means (KM) algorithm is one of the most
popular clustering techniques because of its simplicity and efficiency. However, KM is …

Among the data clustering algorithms, k-means (KM) algorithm is one of the most popular
clustering techniques due to its simplicity and efficiency. However, k-means is sensitive to …

Partitional data clustering with K-means algorithm is the dividing of objects into smaller and
disjoint groups that has the most similarity with objects in a group and most dissimilarity from …

Clustering is the process of grouping data objects into set of disjoint classes called clusters
so that objects within a class are highly similar with one another and dissimilar with the …

Clustering is one of the widely used techniques for data analysis. Also it is a tool to discover
structures from inside of data without any previous knowledge. K-harmonic means (KHM) is …

Clustering is a useful tool to explore data structures and have been employed in many
disciplines. One of the most used techniques for clustering is based on K-means such that …

Clustering is one of the most commonly techniques in Data Mining. Kmeans is one of the
most popular clustering techniques due to its simplicity and efficiency. However, it is …

Clustering is an important task that is used to find subsets of similar objects from a set of
objects such that the objects in the same subsets are more similar than other subsets. Large …

The K-harmonic means clustering algorithm (KHM) is a new clustering method used to
group data such that the sum of the harmonic averages of the distances between each entity …

Data clustering is one of the most important tasks of data mining. This paper aims to
describe an integrated data clustering method based on Imperialist Competitive Algorithm …