The data cluster tendency is an emerging need for exploring the big data cluster analysis
tasks. The data are evaluated based on the number of clusters is known as cluster tendency …

The cluster tendency is one of the major problems in data clustering. Deriving the number of
clusters for an unlabeled dataset is known as the cluster tendency problem. In this paper, the …

Data clustering is the most promising unsupervised technique, and it can be used to partition
the data objects into different clusters. The data objects are placed according to derived …

The Internet of Things (IoT) is playing a vital role in shaping today? s technological world,
including our daily lives. By 2025, the number of connected devices due to the IoT is …

Clustering is widely used technique for grouping of data objects based on similarity features.
The similarity features are derived from the similarity or dissimilarity metrics like Euclidean …

Assessment of clustering tendency is an important first step in crisp or fuzzy cluster analysis.
One tool for assessing cluster tendency is the Visual Assessment of Tendency (VAT) …

Visual methods have been widely studied and used in data cluster analysis. Given a
pairwise dissimilarity matrix\schmi D of a set of n objects, visual methods such as the VAT …

Large-volume and high-dimensional big datasets are being generated quickly. They are
expected to provide data-driven solutions for various pressing challenges such as …

Visual methods have been extensively studied and performed in cluster data analysis. Given
a pairwise dissimilarity matrix D of a set of n objects, visual methods such as Enhanced …

Clusters assessment is a major identified problem in big data clustering. Top big data
partitioning techniques, such as, spherical k-means, Mini-batch-k-means are widely used in …